The effects of NaCl concentration and pH on the stability of hyperthermophilic protein Ssh10b

<p>Abstract</p> <p>Background</p> <p>Hyperthermophiles constitute a group of microorganisms with an optimum growth temperature of between 80°C and 100°C. Although the molecular underpinnings of protein thermostabilization have been the focus of many theoretical and experimental efforts, the properties leading to the higher denaturation temperature of hyperthermophilic proteins are still controversial. Among the large number of factors identified as responsible for the thermostability of hyperthermophilic proteins, the electrostatic interactions are thought to be a universally important factor.</p> <p>Results</p> <p>In this study, we report the effects of pH and salt concentration on the urea-induced denaturation of the protein Ssh10b from a hyperthermophile in low ionic strength buffer. In the absence of NaCl, the unfolding ΔG of the protein increased from about 33 kJ/mol at pH 3 to about 78 kJ/mol at pH 10. At all values of pH, the ΔG increased with increasing NaCl concentration, indicating that salt stabilizes the protein significantly.</p> <p>Conclusion</p> <p>These findings suggests that the increased number of charged residues and ion pairs in the protein Ssh10b from hyperthermophiles does not contribute to the stabilization of the folded protein, but may play a role in determining the denatured state ensemble and also in increasing the denaturation temperature.</p

Testing and Data Reduction of the Chinese Small Telescope Array (CSTAR) for Dome A, Antarctica

The Chinese Small Telescope ARray (hereinafter CSTAR) is the first Chinese astronomical instrument on the Antarctic ice cap. The low temperature and low pressure testing of the data acquisition system was carried out in a laboratory refrigerator and on the 4500m Pamirs high plateau, respectively. The results from the final four nights of test observations demonstrated that CSTAR was ready for operation at Dome A, Antarctica. In this paper we present a description of CSTAR and the performance derived from the test observations.Comment: Accepted Research in Astronomy and Astrophysics (RAA) 1 Latex file and 20 figure

Viruses mobilize plant immunity to deter nonvector insect herbivores.

A parasite-infected host may promote performance of associated insect vectors; but possible parasite effects on nonvector insects have been largely unexplored. Here, we show that Begomovirus, the largest genus of plant viruses and transmitted exclusively by whitefly, reprogram plant immunity to promote the fitness of the vector and suppress performance of nonvector insects (i.e., cotton bollworm and aphid). Infected plants accumulated begomoviral βC1 proteins in the phloem where they were bound to the plant transcription factor WRKY20. This viral hijacking of WRKY20 spatiotemporally redeployed plant chemical immunity within the leaf and had the asymmetrical benefiting effects on the begomoviruses and its whitefly vectors while negatively affecting two nonvector competitors. This type of interaction between a parasite and two types of herbivores, i.e., vectors and nonvectors, occurs widely in various natural and agricultural ecosystems; thus, our results have broad implications for the ecological significance of parasite-vector-host tripartite interactions

Emerging perceptions of teacher quality and teacher development in China

This paper focuses on the work of senior high school teachers in three representative local authority regions of mainland China. It discusses interview and focus group data collected as part of an ESRC/DfID-funded project which examined notions of quality as experienced by key stakeholders (national and local authority policy makers, teachers, head teachers and students). Building on previous international literature this paper gives a more nuanced understanding of quality and effectiveness in teaching by re-examining the dimensions of professional characteristics, classroom practice, school culture and classroom climate from the perceptions of Chinese teachers. Barriers to quality included changing societal patterns, the demands of curriculum reform, and common concerns with structural and funding constraints, which in poorer rural areas are typically reported to lead to low levels of teacher quality, shortages of specialised teachers and a lack of opportunity for good quality professional development

Study on the Micro-structures of Long Fiber through Runner and Cavity in Injection Molding for Reinforced Thermoplastics (FRT)

[[abstract]]Lightweight technology has been applied into many industries especially for automotive to enhance the fuel efficiency. One of most famous methods is applied fiber-reinforced thermoplastics (FRT) technology, it includes short and long fiber-reinforced thermoplastics (FRT) to support lightweight technology. However, the enhancement mechanism by the microstructures of the fibers in FRT is still too complicated to understand. In this study, we designed a benchmark to study the fiber microstructures based on ASTM D638 with dog-bond system. First, we have tried to study how the geometry of cavity influences the fiber orientation during the injection processes. Furthermore, we have paid the attention on the variation of the fiber length distribution as the injection molding processing. Results show that the geometry of cavity has significant effect on the fiber orientation during the injection processes. Since the system has contraction and expansion structure, the orientation tensor component a11 corresponding to the flow direction, will be enhanced and then decreased along the cavity. Moreover, the fiber lengths have dramatically sharp distribution on skin layer when melt goes through the gate into the cavity. It will allow almost 90% lengths are broken through the skin layer. Meanwhile, using numerical visualization from runner to cavity through core layer, there is about 30% length broken during the journey in runner section. Finally, some fiber orientation results are compared with some literature’s. Results showed that our numerical predictions are matched with that of literature quite well in the trend.[[notice]]補正完

Joint Optimization of Ranking and Calibration with Contextualized Hybrid Model

Despite the development of ranking optimization techniques, pointwise loss remains the dominating approach for click-through rate prediction. It can be attributed to the calibration ability of the pointwise loss since the prediction can be viewed as the click probability. In practice, a CTR prediction model is also commonly assessed with the ranking ability. To optimize the ranking ability, ranking loss (e.g., pairwise or listwise loss) can be adopted as they usually achieve better rankings than pointwise loss. Previous studies have experimented with a direct combination of the two losses to obtain the benefit from both losses and observed an improved performance. However, previous studies break the meaning of output logit as the click-through rate, which may lead to sub-optimal solutions. To address this issue, we propose an approach that can Jointly optimize the Ranking and Calibration abilities (JRC for short). JRC improves the ranking ability by contrasting the logit value for the sample with different labels and constrains the predicted probability to be a function of the logit subtraction. We further show that JRC consolidates the interpretation of logits, where the logits model the joint distribution. With such an interpretation, we prove that JRC approximately optimizes the contextualized hybrid discriminative-generative objective. Experiments on public and industrial datasets and online A/B testing show that our approach improves both ranking and calibration abilities. Since May 2022, JRC has been deployed on the display advertising platform of Alibaba and has obtained significant performance improvements.Comment: Accepted at KDD 202

COPR: Consistency-Oriented Pre-Ranking for Online Advertising

Cascading architecture has been widely adopted in large-scale advertising systems to balance efficiency and effectiveness. In this architecture, the pre-ranking model is expected to be a lightweight approximation of the ranking model, which handles more candidates with strict latency requirements. Due to the gap in model capacity, the pre-ranking and ranking models usually generate inconsistent ranked results, thus hurting the overall system effectiveness. The paradigm of score alignment is proposed to regularize their raw scores to be consistent. However, it suffers from inevitable alignment errors and error amplification by bids when applied in online advertising. To this end, we introduce a consistency-oriented pre-ranking framework for online advertising, which employs a chunk-based sampling module and a plug-and-play rank alignment module to explicitly optimize consistency of ECPM-ranked results. A $\Delta NDCG$-based weighting mechanism is adopted to better distinguish the importance of inter-chunk samples in optimization. Both online and offline experiments have validated the superiority of our framework. When deployed in Taobao display advertising system, it achieves an improvement of up to +12.3\% CTR and +5.6\% RPM