Compartment modeling for mammalian protein turnover studies by stable isotope metabolic labeling

Protein turnover studies on a proteome scale based on metabolic isotopic labeling can provide a systematic understanding of mechanisms for regulation of protein abundances and their transient behaviors. At this time, these large-scale studies typically utilize a simple kinetic model to extract protein dynamic information. Although many high-quality, protein isotope incorporation data are available from those experiments, accurate and additionally useful protein dynamic information cannot be extracted from the experimental data by use of the simple kinetic models. In this paper, we describe a formal connection between data obtained from elemental isotope labeling experiments and the well-known compartment modeling, and we demonstrate that an appropriate application of a compartment model to turnover of proteins from mammalian tissues can indeed lead to a better fitting of the experimental data.     

Large-area vapor-phase growth and characterization of MoS(2) atomic layers on a SiO(2) substrate

Atomic-layered MoS(2) is synthesized directly on SiO(2) substrates by a scalable chemical vapor deposition method. The large-scale synthesis of an atomic-layered semiconductor directly on a dielectric layer paves the way for many facile device fabrication possibilities, expanding the important family of useful mono- or few-layer materials that possess exceptional properties, such as graphene and hexagonal boron nitride (h-BN).     

A Bioinspired Platform for Effective Delivery of Protein Therapeutics to the Central Nervous System

Central nervous system (CNS) diseases are the leading cause of morbidity and mortality; their treatment, however, remains constrained by the blood–brain barrier (BBB) that impedes the access of most therapeutics to the brain. A CNS delivery platform for protein therapeutics, which is achieved by encapsulating the proteins within nanocapsules that contain choline and acetylcholine analogues, is reported herein. Mediated by nicotinic acetylcholine receptors and choline transporters, such nanocapsules can effectively penetrate the BBB and deliver the therapeutics to the CNS, as demonstrated in mice and non‐human primates. This universal platform, in general, enables the delivery of any protein therapeutics of interest to the brain, opening a new avenue for the treatment of CNS diseases.     

Performance analysis of a continuous bioreactor for ethanol and acetate synthesis from syngas via <Emphasis Type="Italic">Clostridium ljungdahlii</Emphasis> using exergy concept

In this paper, the exergetic performance of a continuous bioreactor for ethanol and acetate synthesis from syngas via a strictly anaerobic autotrophic bacterium Clostridium ljungdahlii was carried out for the first time. The fermentation process was evaluated using both conventional exergy and eco-exergy principles for measuring the productivity and renewability of the process at various liquid media flow rates. The microorganisms successfully upgraded the syngas into invaluable ethanol and acetate through the Wood–Ljungdahl pathway. The exergy efficiency was found to be in the range of 6.5–77.5 and 6.8–77.5 % during the fermentation using conventional exergy and eco-exergy concepts, respectively. The subtle differences observed in the exergetic parameters using the two exergetic concepts were ascribed to the slow growth rate of the microorganisms. Nevertheless, the eco-exergy concept would strongly be recommended for commercial bioreactor containing living organisms due to the inclusion of the information carried by microorganisms in the exergetic calculation. A desired liquid media flow rate of 0.55 mL/min was found according to a newly defined thermodynamic indictor namely exergetic productivity index. More specifically, the maximum exergetic productivity index of the fermentation process was found to be 8.0 using both approaches when the rate of inflow liquid was adjusted at the optimal value. The results of this study revealed that process yield alone cannot be a reliable performance metric for decision making on the productivity of various biofuel production pathways. Finally, the proposed exergetic framework could assist engineers and researchers to link biochemical and physical knowledge more robustly and to quantify and elucidate the general purpose of productivity and renewability.     

Cross‐Plane Carrier Transport in Van der Waals Layered Materials

The mechanisms of carrier transport in the cross‐plane crystal orientation of transition metal dichalcogenides are examined. The study of in‐plane electronic properties of these van der Waals compounds has been the main research focus in recent years. However, the distinctive physical anisotropies, short‐channel physics, and tunability of cross layer interactions can make the study of their electronic properties along the out‐of‐plane crystal orientation valuable. Here, the out‐of‐plane carrier transport mechanisms in niobium diselenide and hafnium disulfide are explored as two broadly different representative materials. Temperature‐dependent current–voltage measurements are preformed to examine the mechanisms involved. First principles simulations and a tunneling model are used to understand these results and quantify the barrier height and hopping distance properties. Using Raman spectroscopy, the thermal response of the chemical bonds is directly explored and the insight into the van der Waals gap properties is acquired. These results indicate that the distinct cross‐plane carrier transport characteristics of the two materials are a result of material thermal properties and thermally mediated transport of carriers through the van der Waals gaps. Exploring the cross‐plane electron transport, the exciting physics involved is unraveled and potential new avenues for the electronic applications of van der Waals layers are inspired.     

Adaptive routing in wormhole-switched necklace-cubes: Analytical modelling and performance comparison

The necklace hypercube has recently been introduced as an attractive alternative to the well-known hypercube. Previous research on this network topology has mainly focused on topological properties, VLSI and algorithmic aspects of this network. Several analytical models have been proposed in the literature for different interconnection networks, as the most cost-effective tools to evaluate the performance merits of such systems. This paper proposes an analytical performance model to predict message latency in wormhole-switched necklace hypercube interconnection networks with fully adaptive routing. The analysis focuses on a fully adaptive routing algorithm which has been shown to be the most effective for necklace hypercube networks. The results obtained from simulation experiments confirm that the proposed model exhibits a good accuracy under different operating conditions.     

Measurement of low-loss aqueous solutions permittivity with high detection accuracy by a contact and free-label resonance microwave sensor

In this paper, a microwave sensor is designed and built to measure the permittivity of aqueous solutions. The samples used in this experiment are different purities of ethanol mixed with water. Ethanol solution with different purities is a widely used material in industry. Structures of meander, ladder, and T-structure were used to design the sensor. Then the designed sensor is simulated in CST software in range of relative dielectric from 10 to 80. After obtaining the desired answer in the simulation, the proposed sensor is built on the Rogers 4003 substrate, the built-in sensor measured ethanol solution with a purity of 5% to 35% (equivalent to permittivity of 76 to 58), and is showed a sensitivity of 4% and a Q-factor of 3500. The results of simulation and measurement are consistent with each other, and they indicated that the proposed sensor beyond the fluids can be supported and determine their relative dielectrics.     

Performing content-based retrieval of humans using gait biometrics

In order to analyse surveillance video, we need to efficiently explore large datasets containing videos of walking humans. Effective analysis of such data relies on retrieval of video data which has been enriched using semantic annotations. A manual annotation process is time-consuming and prone to error due to subject bias however, at surveillance-image resolution, the human walk (their gait) can be analysed automatically. We explore the content-based retrieval of videos containing walking subjects, using semantic queries. We evaluate current research in gait biometrics, unique in its effectiveness at recognising people at a distance. We introduce a set of semantic traits discernible by humans at a distance, outlining their psychological validity. Working under the premise that similarity of the chosen gait signature implies similarity of certain semantic traits we perform a set of semantic retrieval experiments using popular Latent Semantic Analysis techniques. We perform experiments on a dataset of 2000 videos of people walking in laboratory conditions and achieve promising retrieval results for features such as Sex (mAP  =  14% above random), Age (mAP  =  10% above random) and Ethnicity (mAP  =  9% above random).