Correlation of slurry reactor Fischer-Tropsch yield data

First stage slurry reactor Fischer-Tropsch (FT) yield data from Mobil's two-step pilot plant operations for the DOE have been correlated using a modified Schulz-Flory approach but allowing for changes in the probability of chain growth, , at key product molecular weights. Triple values of are invoked to explain (1) the high methane yield and (2) the very broad molecular weight distribution of the wax fraction, as compared to (3) moderate values of ₂ of between 0.79 and 0.85 for the C₂–C₂₀ hydrocarbons. Over this range, wax yields from 10 to 76 wt% are accommodated, at values of ₃ from 0.90 to 0.98. The second break in the yield-molecular weight curve occurs at the carbon number where most of the component remains in the reactor as liquid rather than leaving as vapor product. It is assumed that this is a function of vapor-liquid equilibrium. The correlation has proven useful in developing a computer model of the FT synthesis loop which is part of a baseline design and economic study for DOE/PETC.     

A Hybrid Strategy-Based Ultra-Narrow Stretchable Microelectrodes with Cell-Level Resolution

Stretchable ultra-narrow (e.g., 10 µm in width) microelectrodes are crucial for the electrophysiological monitoring of single cells providing the fundamental understanding to the working mechanism of neuro network or other electrically functional cells. Current fabrication strategies either focus on the preparation of normal stretchable electrodes with hundreds of micrometers or millimeters in width by using inorganic conductive materials or develop conductive organic polymer gel for ultra-narrow electrodes which suffer from low stretchability and instability for long-term implantation, therefore, it is still highly desirable to explore bio-interfacial ultra-narrow stretchable inorganic electrodes. Herein, a hybrid strategy is reported to prepare ultra-narrow multi-channel stretchable microelectrodes without using photolithography or laser-assisting etching. A 10 µm × 10 µm monitoring window is fabricated with enhanced interfacial impedance by the special rough surface. The stretchability achieves to 120% for this 10 µm-width stretchable electrode. Supported by these superior properties, it is demonstrated that the stretchable microelectrodes can detect electrophysiological signals of single cells in vitro and collect electrophysiological signals more precisely in vivo. The reported strategy will open up the accessible preparation of the fine-size stretchable microelectrode. It will significantly improve the resolution of monitoring and stimulation of inorganic stretchable electrodes.     

Diagnostic performance of edited 2HG MR spectroscopy of central glioma in the clinical environment

Magnetic Resonance Materials in Physics, Biology and Medicine - Oncometabolite D-2-hydroxyglutarate (2HG) is pooled in isocitrate dehydrogenase (IDH)-mutant glioma cells. Detecting 2HG by MR...     

Targeted Nanoparticle Thermometry: A Method to Measure Local Temperature at the Nanoscale Point Where Water Vapor Nucleation Occurs

An optical nanothermometer technique based on laser trapping, moving and targeted attaching an erbium oxide nanoparticle cluster is developed to measure the local temperature. The authors apply this new nanoscale temperature measuring technique (limited by the size of the nanoparticles) to measure the temperature of vapor nucleation in water. Vapor nucleation is observed after superheating water above the boiling point for degassed and nondegassed water. The average nucleation temperature for water without gas is 560 K but this temperature is lowered by 100 K when gas is introduced into the water. The authors are able to measure the temperature inside the bubble during bubble formation and find that the temperature inside the bubble spikes to over 1000 K because the heat source (optically‐heated nanorods) is no longer connected to liquid water and heat dissipation is greatly reduced.     

Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017, it was first used for machine translation tasks and achieved the state of the art at that time. Although the current neural machine translation model can generate high quality translation results, there are still mistranslations and omissions in the translation of key information of long sentences. On the other hand, the most important part in traditional translation tasks is the translation of key information. In the translation results, as long as the key information is translated accurately and completely, even if other parts of the results are translated incorrect, the final translation results’ quality can still be guaranteed. In order to solve the problem of mistranslation and missed translation effectively, and improve the accuracy and completeness of long sentence translation in machine translation, this paper proposes a key information fused neural machine translation model based on Transformer. The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder. After the same encoding as the source language text, it is fused with the output of the source language text encoded by the encoder, then the key information is processed and input into the decoder. With incorporating keyword information from the source language sentence, the model’s performance in the task of translating long sentences is very reliable. In order to verify the effectiveness of the method of fusion of key information proposed in this paper, a series of experiments were carried out on the verification set. The experimental results show that the Bilingual Evaluation Understudy (BLEU) score of the model proposed in this paper on the Workshop on Machine Translation (WMT) 2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset. The experimental results show the advantages of the model proposed in this paper.     

A chondroitin sulfate/keratan sulfate proteoglycan, PG-1000, forms complexes which are concentrated in the reticular laminae of electric organ basement membranes

Previously, we identified PG-1000 as part of a disulfide-linked complex of two large proteoglycans (PG-1000 and the beta component) and three smaller proteins purified from the extracellular matrix of elasmobranch electric organ (Iwata and Carlson, 1991, J. Biol. Chem. 266: 323-333). PG-1000 is a chondroitin sulfate/keratan sulfate proteoglycan with a molecular mass of about 1.2 x 16(6) daltons. When visualized in the electron microscope, PG-1000 has the typical "bottle-brush" appearance expected for a proteoglycan with an average total length of about 345 nm and about 20 chains of approximately 110 nm (Carlson and Wight, 1987, J. Cell Biol. 105: 3075-3086). Using immunocytochemical methods, we now demonstrate that PG-1000 is a component of the interstitial extracellular matrix of the electric organ. PG-1000 immunoreactivity is found throughout the interstitial matrix, but it is highly concentrated in that region of the matrix immediately adjacent to the basal lamina, the reticular lamina. The reticular and basal laminae together form the basement membrane. PG-1000 immunoreactivity is especially apparent on basal laminae that surround nerve fibers and nerve terminals. When the disulfide-linked PG-1000 complexes are purified and examined in the electron microscope following rotary shadowing, they appear as bottle-brush structures which are often attached at a central region and radiate like spokes of a wheel. These aggregates contain two to six proteoglycan monomers. We hypothesize that the PG-1000 complexes are disulfide-stabilized parts of an extended network of linked proteoglycans in the reticular lamina.     

Graph-based quadratic optimization: A fast evolutionary approach

Quadratic optimization lies at the very heart of many structural pattern recognition and computer vision problems, such as graph matching, object recognition, image segmentation, etc., and it is therefore of crucial importance to devise algorithmic solutions that are both efficient and effective. As it turns out, a large class of quadratic optimization problems can be formulated in terms of so-called “standard quadratic programs” (StQPs), which ask for finding the extrema of a quadratic polynomial over the standard simplex. Computationally, the standard approach for attacking this class of problems is to use replicator dynamics, a well-known family of algorithms from evolutionary game theory inspired by Darwinian selection processes. Despite their effectiveness in finding good solutions in a variety of applications, however, replicator dynamics suffer from being computationally expensive, as they require a number of operations per step which grows quadratically with the dimensionality of the problem being solved. In order to avoid this drawback, in this paper we propose a new population game dynamics (InImDyn) which is motivated by the analogy with infection and immunization processes within a population of “players.” We prove that the evolution of our dynamics is governed by a quadratic Lyapunov function, representing the average population payoff, which strictly increases along non-constant trajectories and that local solutions of StQPs are asymptotically stable (i.e., attractive) points. Each step of InImDyn is shown to have a linear time/space complexity, thereby allowing us to use it as a more efficient alternative to standard approaches for solving StQPs and related optimization problems. Indeed, we demonstrate experimentally that InImDyn is orders of magnitude faster than, and as accurate as, replicator dynamics on various applications ranging from tree matching to image registration, matching and segmentation.     

The impact of RFID technology on warehouse process innovation: A pilot project in the TPL industry

Using the value chain model which provides a process view, this longitudinal case study and simulation modeling analysis of a Canadian third-party logistics (TPL) supply chain provides some empirical support for the enabling role of RFID technology in effecting warehouse process innovation and optimization for the focal TPL firm. However, the findings of our study also reveal the RFID technology implementation costs as the key inhibitor of RFID widespread adoption and usage among suppliers. This, in turn, precluded the focal TPL firm from implementing the best optimum RFID solution to create better business value from the RFID project.