Coulomb-coupled quantum-dot thermal transistors

A quantum-dot thermal transistor consisting of three Coulomb-coupled quantum dots coupled to respective electronic reservoirs by tunnel contacts is established. The heat flows through the collector and emitter can be controlled by the temperature of the base. It is found that a small change in the base heat flow can induce a large heat flow change in the collector and emitter. The huge amplification factor can be obtained by optimizing the Coulomb interaction between the collector and the emitter or by decreasing the energy-dependent tunneling rate at the base. The proposed quantum-dot thermal transistor may open up potential applications in low-temperature solid-state thermal circuits at the nanoscale.Comment: 14 pages, 6 figure

Conditional statistical properties of the complex systems having long-range interactions

A new concept of the available force is proposed to investigate the performance of the complex systems having long-range interactions. Since the covariance of average velocity in double time interval and available force equals zero, it is possible to calculate the conditional probability distribution function (CPDF) within the systems. It is found that the asymmetric CPDF of the velocity between two adjacent time intervals can be derived from the symmetrical CPDF between the available force and the double time interval velocity. Two typical currency exchange databases, i.e., EUR/USD and GBP/USD, which collect the minutely opening exchange prices from 1 January 1999 to 31 December 2011, are adopted as examples. It is found that the analytical CPDF needs only six parameters for an arbitrary system. By calculating the CPDF in the currency exchange databases, it is shown that the results are well fitted by our analytical expression. The analytical CPDF can be also used to calculate the conditional expectation and the conditional variance of velocity. Interestingly, the two databases show that the conditional expectation of the velocity between two adjacent time intervals is not monotonic, while the conditional variance tends to monotonic. All of these results are well described by our theory. It is worthwhile to note that the analytical CPDF is a general expression. It is valid not only for current exchange systems but also for any complex systems having long-range interactions and/or long-duration memory.Comment: 21 pages, 4figure

Streamlined protein expression and purification using cleavable self-aggregating tags

<p>Abstract</p> <p>Background</p> <p>Recombinant protein expression and purification remains a fundamental issue for biotechnology. Recently we found that two short self-assembling amphipathic peptides 18A (EWLKAFYEKVLEKLKELF) and ELK16 (LELELKLKLELELKLK) can induce the formation of active protein aggregates in <it>Escherichia coli </it>(<it>E. coli</it>), in which the target proteins retain high enzymatic activities. Here we further explore this finding to develop a novel, facile, matrix-free protein expression and purification approach.</p> <p>Results</p> <p>In this paper, we describe a streamlined protein expression and purification approach by using cleavable self-aggregating tags comprising of one amphipathic peptide (18A or ELK16) and an intein molecule. In such a scheme, a target protein is first expressed as active protein aggregate, separated by simple centrifugation, and then released into solution by intein-mediated cleavage. Three target proteins including lipase A, amadoriase II and β-xylosidase were used to demonstrate the feasibility of this approach. All the target proteins released after cleavage were highly active and pure (over 90% in the case of intein-ELK16 fusions). The yields were in the range of 1.6-10.4 μg/mg wet cell pellet at small laboratory scale, which is comparable with the typical yields from the classical his-tag purification, the IMPACT-CN system (New England Biolabs, Beverly, MA), and the ELP tag purification scheme.</p> <p>Conclusions</p> <p>This tested single step purification is capable of producing proteins with high quantity and purity. It can greatly reduce the cost and time, and thus provides application potentials for both industrial scale up and laboratorial usage.</p

Active protein aggregates induced by terminally attached self-assembling peptide ELK16 in Escherichia coli

<p>Abstract</p> <p>Background</p> <p>In recent years, it has been gradually realized that bacterial inclusion bodies (IBs) could be biologically active. In particular, several proteins including green fluorescent protein, β-galactosidase, β-lactamase, alkaline phosphatase, <smcaps>D</smcaps>-amino acid oxidase, polyphosphate kinase 3, maltodextrin phosphorylase, and sialic acid aldolase have been successfully produced as active IBs when fused to an appropriate partner such as the foot-and-mouth disease virus capsid protein VP1, or the human β-amyloid peptide Aβ42(F19D). As active IBs may have many attractive advantages in enzyme production and industrial applications, it is of considerable interest to explore them further.</p> <p>Results</p> <p>In this paper, we report that an ionic self-assembling peptide ELK16 (LELELKLK)₂was able to effectively induce the formation of cytoplasmic inclusion bodies in <it>Escherichia coli </it>(<it>E. coli</it>) when attached to the carboxyl termini of four model proteins including lipase A, amadoriase II, β-xylosidase, and green fluorescent protein. These aggregates had a general appearance similar to the usually reported cytoplasmic inclusion bodies (IBs) under transmission electron microscopy or fluorescence confocal microscopy. Except for lipase A-ELK16 fusion, the three other fusion protein aggregates retained comparable specific activities with the native counterparts. Conformational analyses by Fourier transform infrared spectroscopy revealed the existence of newly formed antiparallel beta-sheet structures in these ELK16 peptide-induced inclusion bodies, which is consistent with the reported assembly of the ELK16 peptide.</p> <p>Conclusions</p> <p>This has been the first report where a terminally attached self-assembling β peptide ELK16 can promote the formation of active inclusion bodies or active protein aggregates in <it>E. coli</it>. It has the potential to render <it>E. coli </it>and other recombinant hosts more efficient as microbial cell factories for protein production. Our observation might also provide hints for protein aggregation-related diseases.</p

Composite Edible Film Containing Microcapsules Composed of Shrimp-derived Bioactive Peptide Preparation and Preservation Potential

Shrimp body had to face with spoilage and melanosis when it come to food preservation. In this study, a kind of composite edible film (CEF) composed of hydroxypropyl methyl cellulose (HPMC) and shrimp-derived bioactive peptide microcapsule (SBPM), was developed to preserve the body of Penaeus vannamei. First of all, single-factor experiments were conducted by monitoring the mechanical performance and the water vapor permeability (WVP) of CEF, in order to investigate the influence of the dosages of HPMC, glycerol and SBPM, upon the formulation properties and mechanical strength of the film. The FTIR and free radical scavenging capacity of CEF were also determined when the SBPM addition changed and then, the optimum preparation process of CEF was ascertained based on the results mentioned above. In addition, the preservation-effect of CEF on fresh Penaeus vannamei was evaluated by inspecting some important items such as the sensory evaluation, pH, total volatile basic nitrogen (TVB-N) and aerobic bacterial count of shrimp flesh. The results of the single-factor experiments indicated the optimum amounts of HPMC, glycerol and SBPM were 12%, 0.4% and 3%, respectively, and the comprehensive performance of CEF was satisfied under this optimum condition. The antioxidant ability of CEF was excellent when the dosage of SBPM was not less than 3% and, the interaction between SBPM and other membrane fractions was powerful when the addition amount of SBPM came to be 3%~4%, which was indicated by the FTIR results. More importantly, the spoilage of shrimp body could be controlled by covering the body with CEF and, the sensory of seafood might be maintained by this film, as evidenced by the inhibitory effects of CEF on the raising of body pH, the jump of TVB-N and the increase of aerobic bacterial count in shrimp fresh. The quality guarantee period of fresh body in CEF group could be prolonged by 3~4 days as compared with that in unprotected group, while the overall freshness-keeping ablility of CEF was superior to that of HPMC film even PE film, indicating the potent protective effect of CEF on the fresh of Penaeus vannamei

Pre‐symptomatic transmission of novel coronavirus in community settings

We used contact tracing to document how COVID‐19 was transmitted across 5 generations involving 10 cases, starting with an individual who became ill on January 27. We calculated the incubation period of the cases as the interval between infection and development of symptoms. The median incubation period was 6.0 days (interquartile range, 3.5‐9.5 days). The last two generations were infected in public places, 3 and 4 days prior to the onset of illness in their infectors. Both had certain underlying conditions and comorbidity. Further identification of how individuals transmit prior to being symptomatic will have important consequences.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163478/2/irv12773.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163478/1/irv12773_am.pd

Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition

Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific contextual information in various application scenarios. Classic end-to-end models fused with extra language models perform well, but mainly in data matching scenarios and are gradually approaching a bottleneck. In this work, we introduce Seed-ASR, a large language model (LLM) based speech recognition model. Seed-ASR is developed based on the framework of audio conditioned LLM (AcLLM), leveraging the capabilities of LLMs by inputting continuous speech representations together with contextual information into the LLM. Through stage-wise large-scale training and the elicitation of context-aware capabilities in LLM, Seed-ASR demonstrates significant improvement over end-to-end models on comprehensive evaluation sets, including multiple domains, accents/dialects and languages. Additionally, Seed-ASR can be further deployed to support specific needs in various scenarios without requiring extra language models. Compared to recently released large ASR models, Seed-ASR achieves 10%-40% reduction in word (or character, for Chinese) error rates on Chinese and English public test sets, further demonstrating its powerful performance