Programmable base editing of zebrafish genome using a modified CRISPR-Cas9 system.

Precise genetic modifications in model animals are essential for biomedical research. Here, we report a programmable "base editing" system to induce precise base conversion with high efficiency in zebrafish. Using cytidine deaminase fused to Cas9 nickase, up to 28% of site-specific single-base mutations are achieved in multiple gene loci. In addition, an engineered Cas9-VQR variant with 5'-NGA PAM specificities is used to induce base conversion in zebrafish. This shows that Cas9 variants can be used to expand the utility of this technology. Collectively, the targeted base editing system represents a strategy for precise and effective genome editing in zebrafish.The use of base editing enables precise genetic modifications in model animals. Here the authors show high efficient single-base editing in zebrafish using modified Cas9 and its VQR variant with an altered PAM specificity

The use of PCMs for free cooling in buildings

The construction of high-rise buildings has become synonymous with growth and economic prosperity. However, the acceleration in architectural development of China has significantly contributed to the alarming state of environmental disruption. This impact has arisen from land use, energy consumption and the use of other resources such as materials and water, due to the demand for improved living standards and comfort by occupants. EU countries are not strangers to the effects that construction has on the environment, with over 40% of the total final energy consumption by buildings accounted for by the EU. China’s building sector currently accounts for 32.8% of its total energy use, which must not be taken lightly given the massive population of China as well as the rapid rate at which buildings are being constructed. This in turn produces about 50% of global CO2 emissions as well as various other environmentally damaging pollutants (that contribute to global warming). Renewable energy sources include hydropower, wind energy and solar energy or any other new passive cooling or heating technologies. Some of these methods have already widely been used in the EU and China. From the literature, the use of phase-change materials (PCMs) has been shown to help in cooling buildings. Thus, the present research aims to develop new PCM systems to obtain comfortable and healthy conditions in building spaces by reducing any unwanted heat and reducing energy consumption. It will also help with reducing CO2 emissions and minimizing the effects of climate change. Following a literature review and research planning, three different passive PCM systems were designed, and an active PCM slurry cooling pipe system was designed, investigated, modelled then tested under fixed laboratory conditions. Finally, each case was simulated, and the results were compared. The active PCM slurry cooling pipe system was proven the best cooling capacity among the PCM cases. To deepen the investigation, the active PCM pipe system was simulated in a typical building under the real climate conditions. The modelling results show that PCM pipe system helps to reduce the room temperature, the use of PCM pipe system can remain the room temperature in the comfortable temperature interval (23–28°C) for 7 days. In conclusion, the PCM can effectively improve the indoor comfort of the building and reduce the energy consumption of air conditioner system. Between the passive PCM system and active PCM system, the latter demonstrated better performance, and it also had the good results in cooperation with an air conditioner

Smooth estimation of survival and MRL functions under mean residual life order

Let X and Y be two random variables denoting life times having finite means. Let, S 1 , S 2 and M 1 , M 2 denote their survival and MRL functions, respectively. X is said to be smaller than Y in mean residual life order, if and only if [Special characters omitted.] In this thesis smooth estimators for the survival and MRL functions under the above ordering are studied. Nonparametric method given by Hu et al. (2002) has shown good properties, but it is not smooth enough, when the true function is continuous. Chaubey and Sen (1996) have proposed a new approach to smooth survival and density function in stead of the popular kernel method. Following their approach, we introduce two methods for smooth estimation of a survival function based on the two criteria of mean residual life ordering. The strong uniform consistency of the estimators has also been shown here. Numerical studies based on simulation indicate both smooth estimators to be superior to the estimator due to Hu et al. (2002) in terms of bias and MSE in majority of cases

P-odd and CP-odd Four-Quark Contributions to Neutron EDM

In a class of beyond-standard-model theories, CP-odd observables, such as the neutron electric dipole moment, receive significant contributions from flavor-neutral P-odd and CP-odd four-quark operators. However, considerable uncertainties exist in the hadronic matrix elements of these operators strongly affecting the experimental constraints on CP-violating parameters in the theories. Here we study their hadronic matrix elements in combined chiral perturbation theory and nucleon models. We first classify the operators in chiral representations and present the leading-order QCD evolutions. We then match the four-quark operators to the corresponding ones in chiral hadronic theory, finding symmetry relations among the matrix elements. Although this makes lattice QCD calculations feasible, we choose to estimate the non-perturbative matching coefficients in simple quark models. We finally compare the results for the neutron electric dipole moment and P-odd and CP-odd pion-nucleon couplings with the previous studies using naive factorization and QCD sum rules. Our study shall provide valuable insights on the present hadronic physics uncertainties in these observables.Comment: 40 pages, 7 figures. This is the final version. A discussion of the uncertainty of the calculation is adde

It Ain't That Bad: Understanding the Mysterious Performance Drop in OOD Generalization for Generative Transformer Models

Generative Transformer-based models have achieved remarkable proficiency on solving diverse problems. However, their generalization ability is not fully understood and not always satisfying. Researchers take basic mathematical tasks like n-digit addition or multiplication as important perspectives for investigating their generalization behaviors. Curiously, it is observed that when training on n-digit operations (e.g., additions) in which both input operands are n-digit in length, models generalize successfully on unseen n-digit inputs (in-distribution (ID) generalization), but fail miserably and mysteriously on longer, unseen cases (out-of-distribution (OOD) generalization). Studies try to bridge this gap with workarounds such as modifying position embedding, fine-tuning, and priming with more extensive or instructive data. However, without addressing the essential mechanism, there is hardly any guarantee regarding the robustness of these solutions. We bring this unexplained performance drop into attention and ask whether it is purely from random errors. Here we turn to the mechanistic line of research which has notable successes in model interpretability. We discover that the strong ID generalization stems from structured representations, while behind the unsatisfying OOD performance, the models still exhibit clear learned algebraic structures. Specifically, these models map unseen OOD inputs to outputs with equivalence relations in the ID domain. These highlight the potential of the models to carry useful information for improved generalization

Systematic Review on Fabrication, Properties, and Applications of Advanced Materials in Wearable Photoplethysmography Sensors

Photoplethysmography (PPG) technology enables the measurement of multiple physiological and psychological parameters with low‐cost wearable sensors and is reshaping modern healthcare. Advanced materials play a vital role in improving reliability and accuracy of PPG sensors. Recently, various advanced materials have been explored to optimize PPG sensor design, while some challenges exist toward large‐scale validation and mass production. This paper focuses on advanced materials applied in the photodetectors, light sources, and circuits of PPG sensors. The materials are categorized into four groups: inorganic, organic, nanomaterials, and hybrid materials. The properties and fabrication processes are summarized. Other technical details including the mode of operation, measurement sites, testing, and validation are discussed. The merits and limitations of the state of the art are highlighted to provide some suggestions for the future development of PPG sensors based on advanced materials