Why Do Computers Depreciate?

The value of installed computers falls rapidly and therefore computers have a very high user cost. The paper provides a complete account of the non-financial user cost of personal computers -- decomposing it into replacement cost change, obsolescence, instantaneous depreciation, and age-related depreciation. The paper uses data on the resale price of computers and a hedonic price index for new computers to achieve this decomposition. Once obsolescence is taken into account, age-related depreciation -- which is often identified as deterioration -- is estimated to be negligible. While the majority of the loss in value of used computers comes from declines in replacement cost, this paper shows the second most important source of decline in value is obsolescence. Obsolescence is accelerated by the decline in replacement cost of computers. Cheaper computing power drives developments in software and networks that make older computers less productive even though their original functionality remains intact.

System for and method of performing evaluation techniques on a log or round timber

A system for and method of evaluating a log. The system includes an analysis module having at least one input terminal connectable to the at least one input device. The at least one input terminal is operable to receive at least one signal representing at least one measured property of the log and at least one determined parameter of the log determined in response to an energy being applied to the log. The analysis module further includes a processor coupled to the at least one input terminal. The processor determines a predictive modulus of elasticity (MOE) of the log based at least in part on the at least one measured property and the at least one sensed parameter. The analysis module also includes an output terminal coupled to the processor and connectable to an output device. The output terminal transmits a third signal representing the predictive MOE.https://digitalcommons.mtu.edu/patents/1042/thumbnail.jp

An Antibiotic-Responsive Mouse Model of Fulminant Ulcerative Colitis

Paul Allen and colleagues describe the development of a mouse model of fulminant ulcerative colitis with multiple genetic hits in immune regulation which can be moderated by anti-cytokine therapy and broad-spectrum antibiotics

Broad Spectrum Pro-Quorum-Sensing Molecules as Inhibitors of Virulence in Vibrios

Quorum sensing (QS) is a bacterial cell-cell communication process that relies on the production and detection of extracellular signal molecules called autoinducers. QS allows bacteria to perform collective activities. Vibrio cholerae, a pathogen that causes an acute disease, uses QS to repress virulence factor production and biofilm formation. Thus, molecules that activate QS in V. cholerae have the potential to control pathogenicity in this globally important bacterium. Using a whole-cell high-throughput screen, we identified eleven molecules that activate V. cholerae QS: eight molecules are receptor agonists and three molecules are antagonists of LuxO, the central NtrC-type response regulator that controls the global V. cholerae QS cascade. The LuxO inhibitors act by an uncompetitive mechanism by binding to the pre-formed LuxO-ATP complex to inhibit ATP hydrolysis. Genetic analyses suggest that the inhibitors bind in close proximity to the Walker B motif. The inhibitors display broad-spectrum capability in activation of QS in Vibrio species that employ LuxO. To the best of our knowledge, these are the first molecules identified that inhibit the ATPase activity of a NtrC-type response regulator. Our discovery supports the idea that exploiting pro-QS molecules is a promising strategy for the development of novel anti-infectives

Towards Experimental Handbooks in Catalysis

The “Seven Pillars” of oxidation catalysis proposed by Robert K. Grasselli represent an early example of phenomenological descriptors in the field of heterogeneous catalysis. Major advances in the theoretical description of catalytic reactions have been achieved in recent years and new catalysts are predicted today by using computational methods. To tackle the immense complexity of high-performance systems in reactions where selectivity is a major issue, analysis of scientific data by artificial intelligence and data science provides new opportunities for achieving improved understanding. Modern data analytics require data of highest quality and sufficient diversity. Existing data, however, frequently do not comply with these constraints. Therefore, new concepts of data generation and management are needed. Herein we present a basic approach in defining best practice procedures of measuring consistent data sets in heterogeneous catalysis using “handbooks”. Selective oxidation of short-chain alkanes over mixed metal oxide catalysts was selected as an example.DFG, 390540038, EXC 2008: Unifying Systems in Catalysis "UniSysCat