Using partial isolation rings to test core-based designs

A partial isolation ring provides the same fault coverage as a full isolation ring but avoids adding multiplexers on critical timing paths and reduces area overhead. The authors examine several partial isolation ring selection strategies that vary in computational complexity     

Amyloid Self‐Assembly of hIAPP8‐20 via the Accumulation of Helical Oligomers, α‐Helix to β‐Sheet Transition,and Formation of β‐Barrel Intermediates

The self‐assembly of human islet amyloid polypeptide (hIAPP) into β‐sheet‐rich nanofibrils is associated with the pathogeny of type 2 diabetes. Soluble hIAPP is intrinsically disordered with N‐terminal residues 8–17 as α‐helices. To understand the contribution of the N‐terminal helix to the aggregation of full‐length hIAPP, here the oligomerization dynamics of the hIAPP fragment 8–20 (hIAPP8‐20) are investigated with combined computational and experimental approaches. hIAPP8‐20 forms cross‐β nanofibrils in silico from isolated helical monomers via the helical oligomers and α‐helices to β‐sheets transition, as confirmed by transmission electron microscopy, atomic force microscopy, circular dichroism spectroscopy, Fourier transform infrared spectroscopy, and reversed‐phase high performance liquid chromatography. The computational results also suggest that the critical nucleus of aggregation corresponds to hexamers, consistent with a recent mass‐spectroscopy study of hIAPP8‐20 aggregation. hIAPP8‐20 oligomers smaller than hexamers are helical and unstable, while the α‐to‐β transition starts from the hexamers. Converted β‐sheet‐rich oligomers first form β‐barrel structures as intermediates before aggregating into cross‐β nanofibrils. This study uncovers a complete picture of hIAPP8‐20 peptide oligomerization, aggregation nucleation via conformational conversion, formation of β‐barrel intermediates, and assembly of cross‐β protofibrils, thereby shedding light on the aggregation of full‐length hIAPP, a hallmark of pancreatic beta‐cell degeneration.     

Carum copticum Benth. & Hook., essential oil chemotypes

Carum copticum Benth. & Hook is a popular spice and a traditional flavor that is used in Iran. The fruits of C. copticum have several therapeutic effects including carminative, diuretic and anti-vomiting effects. There are some reports on the chemical composition of C. copticum fruits essential oil. In our research the results of GC–MS analyses of the essential oil from C. copticum fruits and differences among various reports were described. Major constitutes of the oil were thymol (54.50%), γ-terpinene (26.10%) and p-cymene (22.10%). Comparison of the result from this study with other reports indicates that C. copticum have thymol and carvacrol chemotypes.     

Study on governing parameters of thermal history during underwater friction stir welding

Underwater friction stir welding (FSW) could widely extend the submarine applications of solid-state welding methods. Since, in the case of underwater FSW, the temperature field exhibits profound effects on the acquired weld properties, studying the corresponding governing parameters is of high priority. With this end in view, in order to explicate the heat generated by the FSW tool, the applied forces on the FSW tool, as the unknown parameters in the heat generation equation, are obtained. Subsequently, the heat transfer of the surrounding fluid, which dictates the heat transfer through the workpiece is investigated. The results reveal that upon comparison to FSW in air medium, both translational and axial forces considerably increase leading to greater heat generated by the underwater FSW tool. However, the peak temperature in each point during underwater welding declines dramatically (40 %) compared to the in-air welding, which can be attributed to the extreme boiling heat transfer of water on both the workpiece and FSW tool. This behavior may be the main reason for the acquired mechanical properties of the underwater-welded AA7075-T6 plates as a precipitating hardening alloy. The mentioned heat transfer is non-uniform over the workpiece and comprises different types including nucleation and transition boiling as well as free convection. Furthermore, the study of the mechanical characteristics revealed that underwater welding leads to joints with more strength and lower ductility compared to those obtained by in-air welding.     

An effective characterization procedure for petroleum reservoir fluids using molecular type methods and cubic equations of state

Two eminent molecular type composition methods (paraffins, naphthenes, and aromatics [PNA] and saturates, aromatics, and polynuclear aromatics [SAP]) are employed to construct new characterization procedures for predicting the phase behaviour of petroleum fluids using a modified Peng–Robinson equation of state. The PNA and SAP methods divide a petroleum fraction into (PNA) and (SAP) homologous groups, respectively. Two generalized models are developed to predict the physical properties ($\mathrm{Mw},\mathrm{SG},T_b$) and equation of state (EOS) parameters ($T_c,P_c,\omega$) for both PNA and SAP sub-fractions. Each generalized model covers 18 different correlations in a single mathematical form that enables the model to return 18 outputs for PNA and SAP sub-fraction parameters. A new lumping method is also developed to convert triple PNA or SAP pseudo-components into single characterized fractions. Accordingly, seven different characterization procedures are introduced and compared with one another. The first two procedures are completely constructed based on the proposed models, and the other procedures encompass the models already developed. The results obtained from the simulation of the differential liberation test for 12 diverse reservoir fluids and bubble pressure prediction for 40 oil samples revealed that the first two methods (1 and 2) could enhance the abilities of the traditional characterization procedures for reservoir fluid modelling. The mean value of average absolute relative deviations (AARDs) over a total of 52 oil samples is about 6.5% for the proposed methods and is about 13.2% for the best previously existing methods. Moreover, an efficient workflow is provided for the parameter tuning process, which is notably capable of reducing the level of prediction errors using only three adjustable parameters.