Modeling and optimization of cold extrusion process by using response surface methodology and metaheuristic approaches

Obtaining the optimal extrusion process parameters by integration of optimization techniques was crucial and continuous engineering task in which it attempted to minimize the tool load. The tool load should be minimized as higher extrusion forces required greater capacity and energy. It may lead to increase the chance of part defects, die wear and die breakage. Besides, optimization may help to save the time and cost of producing the final product, in addition to produce better formability of work material and better quality of the finishing product. In this regard, this study aimed to determine the optimal extrusion process parameters. The minimization of punch load was the main concern, in such a way that the structurally sound product at minimum load can be achieved. Minimization of punch load during the extrusion process was first formulated as a nonlinear programming model using response surface methodology in this study. The established extrusion force model was then taken as the fitness function. Subsequently, the analytical approach and metaheuristic algorithms, specifically the particle swarm optimization, cuckoo search algorithm (CSA) and flower pollination algorithm, were applied to optimize the extrusion process parameters. Performance assessment demonstrated the promising results of all presented techniques in minimizing the tool loading. The CSA, however, gave more persistent optimization results, which was validated through statistical analysi

All-electric all-semiconductor spin field-effect transistors.

The spin field-effect transistor envisioned by Datta and Das opens a gateway to spin information processing. Although the coherent manipulation of electron spins in semiconductors is now possible, the realization of a functional spin field-effect transistor for information processing has yet to be achieved, owing to several fundamental challenges such as the low spin-injection efficiency due to resistance mismatch, spin relaxation and the spread of spin precession angles. Alternative spin transistor designs have therefore been proposed, but these differ from the field-effect transistor concept and require the use of optical or magnetic elements, which pose difficulties for incorporation into integrated circuits. Here, we present an all-electric and all-semiconductor spin field-effect transistor in which these obstacles are overcome by using two quantum point contacts as spin injectors and detectors. Distinct engineering architectures of spin-orbit coupling are exploited for the quantum point contacts and the central semiconductor channel to achieve complete control of the electron spins (spin injection, manipulation and detection) in a purely electrical manner. Such a device is compatible with large-scale integration and holds promise for future spintronic devices for information processing.We thank C.-W. Chang, C.-C. Cheng, M. Fletcher, S. N. Holmes, C.-T. Liang, S.-T. Lo and J. R. Petta for discussion and/or technical assistance on device fabrication and measurements. This work was supported by the Ministry of Science and Technology (Taiwan), the Headquarters of University Advancement at the National Cheng Kung University, and the Engineering and Physical Sciences Research Council (UK).This is the accepted manuscript. The final version is available at http://www.nature.com/nnano/journal/v10/n1/full/nnano.2014.296.htm

A Statistics-Based And An Simple Physics-Based Models Toward An Operational And Early Flood Warning System

Life and property losses because of disasters such as flood and landslide are getting dramatic increases for past years. Frequent extreme weather events have even worsened the damages globally. Given sufficient information in advance, disaster preparedness and management can be well-settled. The damages and losses can be mitigated and even prevented. An early disaster warning system with enough leadtimes is essential for decision-makers to take prevented measures and execute cautions. This study proposed a prototype of an early disaster warning system which issues warnings for rainfall related disasters such as flood and landslide. Using ensemble quantitative precipitation forecasts, the system could estimate the disaster risk and issue possible threat warnings up to 72 hours in advance. The system is a statistics-based, instead of physics-based model to meet the real time operational needs. The advantage is to provide the information and issue the warnings rapidly which helps the decision-makers have more time to deploy the rescue forces such as manpower and water pumps. For the flood forecasts, the proposed system integrated artificial intelligence with historical records, design capacity of storm sewer system, and threshold rainfall to identify the high risk areas in a township level. A simple physics-based model then was imposed to identify possible flooding areas downscale to the village level. The landslide susceptibility model was developed using the logistic regression that used rainfall, topography and geology as the geo-environment variables affecting slope stability. According to occurrence of disaster and available observed records, the proposed system used typhoon events from 2010 to 2012 in Pingtung County, Taiwan to evaluate the performance. The spatial and temporal comparisons with observations demonstrated promising potential as a valuable reference for better emergency response to alleviate the loss of lives and property

Development of pollen mediated activation tagging system for Phalaenopsis and Doritaenopsis

Abstract In the present study, a novel plant transformation system for Doritaenopsis and Phalaenopsis has been developed. The pollen-mediated activation tagging system was established by artificial pollination. The pollens, co-cultured with Agrobacterium tumefaciens strain EHA105 harbouring an activation tagging vector (pTAG-8), were used for pollination. In order to optimize the transformation efficiency, several factors (concentration of A. tumefaciens, concentration of acetosyringone during co-cultivation and the duration of co-cultivation) known to influence Agrobacterium-mediated DNA transfer were examined. A concentration of 0.5-1 x 108 CFU/ml for A. tumefaciens, 0.1 mM acetosyringone, and 6 hrs of co-culture period were found to be the optimal condition for high transformation efficiency. Integration of T-DNA into the genome of putative transgenic plants was confirmed by PCR and DNA blot analyses. Single copy of the transgene was observed in all transgenic plants analyzed. Most of the transgenic plants had a morphologically normal phenotype and the overall capsule formation efficiency was similar to control plant. Our results showed a new approach of genetic transformation in orchids and this method can be employed for genetic improvement of the orchids

Finding a Fair Land Dispute Settlement Mechanism Between Adat Law Community Vs. Investor

Land utilization for investment in local areas raises various land related problems that ends with conflicts within the community. A conflict that occurs, usually begins with the management of communal land “tanah ulayat” within the adat law community environment, and in this case, land utilization that is managed by the third party (investors). The basic problem is the difference of perception and expectations toward the company that exists in the land which is claimed by the community. Both parties have their own claim on the land based on each legal systems, in this situation adat law or local law faced with state law which is used by investors. So far, the Indonesian government has yet to have legal grounds in giving a directions for land dispute/conflict settlement mechanism. This paper attempts to give an input regarding a land dispute settlement mechanism that can be accepted for all disputing parties. The paper features critical analysis using legal pluralism approach towards related government policies and technical regulations in the ministerial level. These regulations, among others are, Minister of Agrarian Regulation No. 5 of 1999 on the Guidance for Dispute Settlement of Communal Land Rights, and Ministry of Agrarian and Spatial Affairs Regulation No. 9 of 2015 on Procedures of Appointment of Communal Land Rights for Adat Law Community and Communities Located in certain regions, also the draft of Law regarding Recognition and Protection of Adat Law Community

High serum levels of procalcitonin and soluble TREM-1 correlated with poor prognosis in pulmonary tuberculosis

SummaryObjectivesComparisons of procalcitonin (PCT), C-reactive protein (CRP), and soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) would expand our knowledge of which biomarker is the best predictor for outcomes of patients with pulmonary tuberculosis (PTB).MethodsWe prospectively enrolled 243 PTB patients, in whom PCT, CRP, and sTREM-1 measurement were performed to evaluate their prognostic value for 6-month mortality.ResultsSerum PCT, CRP, and sTREM-1 levels on diagnosis of PTB were significantly higher in nonsurvivors (2.22 ± 6.22 vs. 0.13 ± 0.31 ng/mL, P = 0.043; 42.1 ± 59.4 vs. 12.5 ± 29.1 mg/L, P = 0.004; 332 ± 362 vs. 128 ± 98 pg/mL, P = 0.001, respectively) as compared with 6-month survivors. In multivariate Cox regression analysis, PCT ≧0.5 ng/mL (hazard ratio 4.13, 95% CI, 1.99–8.58) and sTREM-1 ≧129 pg/mL (hazard ratio 3.39, 95% CI, 1.52–7.58) remained independent mortality predictors. Serum PCT and sTREM-1 levels above the cutoffs were also associated with the presence of disseminated tuberculosis.ConclusionsAmong PTB patients, higher PCT, CRP, and sTREM-1 levels are observed in nonsurvivors than in 6-month survivors. Serum levels of PCT and sTREM-1 over the cutoffs are independently associated with a poor outcome. In addition, higher PCT and sTREM-1 levels would raise the clinical suspicion of disseminated tuberculosis

Susceptibility of Human Embryonic Stem Cell-Derived Neural Cells to Japanese Encephalitis Virus Infection

Pluripotent human embryonic stem cells (hESCs) can be efficiently directed to become immature neuroepithelial precursor cells (NPCs) and functional mature neural cells, including neurotransmitter-secreting neurons and glial cells. Investigating the susceptibility of these hESCs-derived neural cells to neurotrophic viruses, such as Japanese encephalitis virus (JEV), provides insight into the viral cell tropism in the infected human brain. We demonstrate that hESC-derived NPCs are highly vulnerable to JEV infection at a low multiplicity of infection (MOI). In addition, glial fibrillary acid protein (GFAP)-expressing glial cells are also susceptible to JEV infection. In contrast, only a few mature neurons were infected at MOI 10 or higher on the third day post-infection. In addition, functional neurotransmitter-secreting neurons are also resistant to JEV infection at high MOI. Moreover, we discover that vimentin intermediate filament, reported as a putative neurovirulent JEV receptor, is highly expressed in NPCs and glial cells, but not mature neurons. These results indicate that the expression of vimentin in neural cells correlates to the cell tropism of JEV. Finally, we further demonstrate that membranous vimentin is necessary for the susceptibility of hESC-derived NPCs to JEV infection

Extreme Active Molecular Jets in L1448C

The protostellar jet driven by L1448C was observed in the SiO J=8-7 and CO J=3-2 lines and 350 GHz dust continuum at ~1" resolution with the Submillimeter Array (SMA). A narrow jet from the northern source L1448C(N) was observed in the SiO and the high-velocity CO. The jet consists of a chain of emission knots with an inter-knot spacing of ~2" (500 AU) and a semi-periodic velocity variation. The innermost pair of knots, which are significant in the SiO map but barely seen in the CO, are located at ~1" (250 AU) from the central source, L1448C(N). Since the dynamical time scale for the innermost pair is only ~10 yr, SiO may have been formed in the protostellar wind through the gas-phase reaction, or been formed on the dust grain and directly released into the gas phase by means of shocks. It is found that the jet is extremely active with a mechanical luminosity of ~7 L_sun, which is comparable to the bolometric luminosity of the central source (7.5 L_sun). The mass accretion rate onto the protostar derived from the mass-loss rate is ~10^{-5} M_sun/yr. Such a high mass accretion rate suggests that the mass and the age of the central star are 0.03-0.09 M_sun and (4-12)x10^3 yr, respectively, implying that the central star is in the very early stage of protostellar evolution. The low-velocity CO emission delineates two V-shaped shells with a common apex at L1448C(N). The kinematics of these shells are reproduced by the model of a wide opening angle wind. The co-existence of the highly-collimated jets and the wide-opening angle shells can be explained by the unified X-wind model" in which highly-collimated jet components correspond to the on-axis density enhancement of the wide-opening angle wind. The CO $J$=3--2 map also revealed the second outflow driven by the southern source L1448C(S) located at ~8.3" (2000 AU) from L1448C(N).Comment: 45 pages, 13 figures, Accepted for the publication in the Astrophysical Journa

Diameter prediction and optimization of hot extrusion-synthesized polypropylene filament using statistical and soft computing techniques

In this study, statistical and soft computing techniques were developed to investigate effect of process parameters on diameter of extruded filament made of polypropylene in hot extrusion. A multi-factors experiment was designed with process parameters of screw speed, roller speed and die temperature. According to the design matrix, twenty four experiments were conducted. The diameter of the extruded plastic filament was measured in each experiment. Subsequently, statistical analysis was used to identify significant factors on diameter of extruded filament. Predictive models of response surface methodology (RSM) and radial basis function neural network(RBFNN)were applied to predict the diameter of extruded filament. The optimal process parameters to maintain the diameter of the filament closest to the target value were identified using the cuckoo search algorithm (CSA), and particle swarm optimization (PSO). Performance analysis demonstrated the superior predictive ability of both models, in which the prediction errors of 0.0245 and 0.0029 (in terms of mean squared error) were obtained byRSM and RBFNN, respectively. Considering the optimization methods, the optimization approaches of using CSA and PSO were promising, in which average relative error of 1.28% was obtained in confirmation tests