Microstructure of severely deformed metals from X-ray line profile analysis

Two essentially different materials, cubic Ti(49.8)Ni(50.2) shape memory alloy and hexagonal AZ91 Mg alloy, were deformed by equal channel angular pressing (ECAP). The microstructure developed as a result of severe plastic deformation was studied by X-ray line profile analysis. The correlation between the microstructure and the mechanical behavior was also investigated. Below 100 degrees C the tensile strength of the Mg alloy increased as a consequence of the increase of the dislocation density owing to ECAP. Above 200 degrees C the strength decreased and the ductility increased as a result of the breakage of the Al(12)Mg(17) precipitates due to ECAP. The analysis of the dislocation contrast factors of Ti(49.8)Ni(50.2) revealed that {110} dislocations with line vector formed during ECAP

Solutions of Conformal Turbulence on a Half Plane

Exact solutions of conformal turbulence restricted on a upper half plane are obtained. We show that the inertial range of homogeneous and isotropic turbulence with constant enstrophy flux develops in a distant region from the boundary. Thus in the presence of an anisotropic boundary, these exact solutions of turbulence generalize Kolmogorov's solution consistently and differ from the Polyakov's bulk case which requires a fine tunning of coefficients. The simplest solution in our case is given by the minimal model of $p=2, q=33$ and moreover we find a fixed point of solutions when $p,q$ become large.Comment: 10pages, KHTP-93-07, SNUCTP-93-3

Free Energy Approach to the Formation of an Icosahedral Structure during the Freezing of Gold Nanoclusters

The freezing of metal nanoclusters such as gold, silver, and copper exhibits a novel structural evolution. The formation of the icosahedral (Ih) structure is dominant despite its energetic metastability. This important phenomenon, hitherto not understood, is studied by calculating free energies of gold nanoclusters. The structural transition barriers have been determined by using the umbrella sampling technique combined with molecular dynamics simulations. Our calculations show that the formation of Ih gold nanoclusters is attributed to the lower free energy barrier from the liquid to the Ih phases compared to the barrier from the liquid to the face-centered-cubic crystal phases

Treatment of Metal Wastes Containing Ni, Co and Mn with Deep-Sea Manganese Nodules

The spent Ni-Cd battery and the spent catalyst containing cobalt were treated by reductionsmelting process with deep-sea Manganese nodules for recovery of nickel and cobalt metals. The nickel in the spent Ni-Cd battery could be recovered with adding 5% coke as a reducing agent regardless of the amount of battery added. However, to recover cobalt from the spent catalyst, it is required to add more coke for reduction of cobalt oxide in the catalyst. The treatment of metal wastes with manganese nodules can contribute to lower the cost for the proce-ssing of nodules and to facilitate the recycling of metal wastes

Early Recognition of Burn- and Trauma-Related Acute Kidney Injury: A Pilot Comparison of Machine Learning Techniques.

Severely burned and non-burned trauma patients are at risk for acute kidney injury (AKI). The study objective was to assess the theoretical performance of artificial intelligence (AI)/machine learning (ML) algorithms to augment AKI recognition using the novel biomarker, neutrophil gelatinase associated lipocalin (NGAL), combined with contemporary biomarkers such as N-terminal pro B-type natriuretic peptide (NT-proBNP), urine output (UOP), and plasma creatinine. Machine learning approaches including logistic regression (LR), k-nearest neighbor (k-NN), support vector machine (SVM), random forest (RF), and deep neural networks (DNN) were used in this study. The AI/ML algorithm helped predict AKI 61.8 (32.5) hours faster than the Kidney Disease and Improving Global Disease Outcomes (KDIGO) criteria for burn and non-burned trauma patients. NGAL was analytically superior to traditional AKI biomarkers such as creatinine and UOP. With ML, the AKI predictive capability of NGAL was further enhanced when combined with NT-proBNP or creatinine. The use of AI/ML could be employed with NGAL to accelerate detection of AKI in at-risk burn and non-burned trauma patients

INFORMATION SYSTEMS OUTSOURCING: A MIXED INTEGER PROGRAMMING ANALYSIS

In the recent past, the trend toward outsourcing has become a major information systems phenomenon. Outsourcing is the subcontracting of various information systems subfunctions such as managing of data centers, operations, hardware support software maintenance, and even application software by user-firms to either incumbent vendors or outside vendors. Outsourcing is therefore emerging as a key approach for managing infonnation systems functions. In this research, we investigate the outsourcing bidding process pertinent to the selection of one subcontractor by a userfirm. We analyze bidding situations where the bidders have different levels of expertise and cost structures. The theoretical foundations for this research lie iii the theory of mechanism design (Myerson 1983), as well as the theory of imperfect information (Philips 1988) and incentive design (Ledyard 1989; McAfee 1986). We build a mixed integer programming model to represent what happens in an outsourcing bidding context involving a user-firm, an incumbent firm, and a challenger firm and explore the implications. The analysis is conducted over two different time horizons called the ex ante and the ex post periods. Two mixed-integer programming models are presented for two time horizons (in developing the model, we follow Kreps 1990). To reflect the different levels of expertise and cost structures of bidders, a discrete probability distribution is assigned to each bidder to approximate a bidder\u27 s true cost. A bidder\u27s true cost is private information, but its probability distribution is assumed to be common knowledge. An incumbent firm is assumed to have cost advantages over other bidders as a result of being familiar with the information needs of the user-firm. Therefore, the incumbent firm is assigned a cost probability distribution that is skewed toward low cost. The competing bidder\u27s cost structure is skewed toward high cost. The objective function of each model is formulated so as to minimize the expected cost subject to participation, and truthtelling constraints. Participation constraints indicate that each bidder participates only if a positive profit is given by the user-firm. Truth-telling constmints denote that each bidder prefers telling the truth to misrepresentation. The preliminary results of the models suggest that a policy of awarding incentives and levying penalties needs to be followed by the user firm. The results show that in order to induce the bidders to behave truthfully, some penalties would have to be levied and incentives would have to be provided. For example, if both the incumbent bidder and the challenger bid the same. the challenger is awarded the bid. If the incumbent firm is found to be inflating quotes, a penalty would have to be levied against the incumbent in the sense that the contract would be awarded to the challenger. Finally, in order to reward the bidder who quotes the true costs, subsides would have to be awarded. Thus, the models provide theoretical justification and guidelines for bidding behavior practices in the real world. Interestingly, both the ex-ante and ex-post models based on Krep\u27s assumptions show identical results. Implications of this finding need to be further explored in future research

Memory and superposition in a spin glass

Non-equilibrium dynamics in a Ag(Mn) spin glass are investigated by measurements of the temperature dependence of the remanent magnetisation. Using specific cooling protocols before recording the thermo- or isothermal remanent magnetisations on re-heating, it is found that the measured curves effectively disclose non-equilibrium spin glass characteristics such as ageing and memory phenomena as well as an extended validity of the superposition principle for the relaxation. The usefulness of this "simple" dc-method is discussed, as well as its applicability to other disordered magnetic systems.Comment: REVTeX style; 8 pages, 4 figure

Propagation of Exchange Bias in CoFe/FeMn/CoFe Trilayers

CoFe/FeMn, FeMn/CoFe bilayers and CoFe/FeMn/CoFe trilayers were grown in magnetic field and at room temperature. The exchange bias field $H_{eb}$ depends strongly on the order of depositions and is much higher at CoFe/FeMn than at FeMn/CoFe interfaces. By combining the two bilayer structures into symmetric CoFe/FeMn($t_\mathrm{FeMn}$)/CoFe trilayers, $H_{eb}^t$ and $H_{eb}^b$ of the top and bottom CoFe layers, respectively, are both enhanced. Reducing $t_\mathrm{FeMn}$ of the trilayers also results in enhancements of both $H_{eb}^b$ and $H_{eb}^t$. These results evidence the propagation of exchange bias between the two CoFe/FeMn and FeMn/CoFe interfaces mediated by the FeMn antiferromagnetic order

SPEAR Far Ultraviolet Spectral Images of the Cygnus Loop

We present far-ultraviolet (FUV) spectral images, measured at C IV 1550, He II 1640, Si IV+O IV] 1400, and O III] 1664, of the entire Cygnus Loop, observed with the Spectroscopy of Plasma Evolution from Astrophysical Radiation (SPEAR) instrument, also known as FIMS. The spatial distribution of FUV emission generally corresponds with a limb-brightened shell, and is similar to optical, radio and X-ray images. The features found in the present work include a ``carrot'', diffuse interior, and breakout features, which have not been seen in previous FUV studies. Shock velocities of 140-160 km/s is found from a line ratio of O IV] to O III], which is insensitive not only to resonance scattering but also to elemental abundance. The estimated velocity indicates that the fast shocks are widespread across the remnant. By comparing various line ratios with steady-state shock models, it is also shown that the resonance scattering is widespread.Comment: 13 pages, 3 figures, 1 table, accepted for publication in ApJ