Inductive Data Types Based on Fibrations Theory in Programming

Traditional methods including algebra and category theory have some deficiencies in analyzing semantics properties and describing inductive rules of inductive data types, we present a method based on Fibrations theory aiming at those questions above. We systematically analyze some basic logical structures of inductive data types about a fibration such as re-indexing functor, truth functor and comprehension functor, make semantics models of non-indexed fibration, single-sorted indexed fibration and many-sorted indexed fibration respectively. On this basis, we thoroughly discuss semantics properties of fibred, single-sorted indexed and many-sorted indexed inductive data types, and abstractly describe their inductive rules with universality. Furthermore, we briefly introduce applications of the three inductive dana types for analyzing semantics properties and describing inductive rules based on Fibrations theory via some examples. Compared with traditional methods, our works have the following three advantages. Firstly, brief descriptions and flexible expansibility of Fibrations theory can analyze semantics properties of inductive data types accurately, whose semantics are computed automatically. Secondly, superior abstractness of Fibrations theory does not rely on particular computing environments to depict inductive rules of inductive data types with universality. Thirdly, its rigorousness and consistence provide sound basis for testing and maintenance of software development

Large Ecosystem Service Benefits of Assisted Natural Regeneration

China manages the largest monoculture plantations in the world, with 24% being Chinese fir plantations. Maximizing the ecosystem services of Chinese fir plantations has important implications in global carbon cycle and biodiversity protection. Assisted natural regeneration (ANR) is a practice to convert degraded lands into more productive forests with great ecosystems services. However, the quantitative understanding of ANR ecosystem service benefits is very limited. We conducted a comprehensive field manipulation experiment to evaluate the ANR potentials. We quantified and compared key ecosystem services including surface runoff, sediment yield, dissolved organic carbon export, plant diversity, and aboveground carbon accumulation of ANR of secondary forests dominated by Castanopsis carlesii to that of Chinese fir and C. carlesii plantations. Our results showed that ANR of C. carlesii forest reduced surface runoff and sediment yield up to 50% compared with other young plantations in the first 3 years and substantially increased plant diversity. ANR also reduced the export of dissolved organic carbon by 60–90% in the first 2 years. Aboveground biomass of the young ANR forest was approximately 3–4 times of that of other young plantations, while aboveground biomass of mature ANR forests was approximately 1.4 times of that of mature Chinese fir plantations of the same age. If all Chinese fir plantations in China were replaced by ANR forests, potentially 0.7 Pg more carbon will be stored in aboveground in one rotation (25 years). The results indicate that ANR triggers positive feedbacks among soil and water conservation, biodiversity protection, and biomass accumulation and thereby enhances ecosystem services

GRIK3 rs490647 is a Common Genetic Variant between Personality and Subjective Well-being in Chinese Han Population

Personality and subjective well-being (SWB) have been suggested to be strongly related in previous studies. This study was intended to confirm the relationship between personality and SWB and tried to seek out the genetic variants which underlie both personality and SWB. The subjects were 890 participants from Chinese Han population. We evaluated their personality using the Big Five Inventory (BFI) and used the Satisfaction With Life Scale (SWLS) to reflect their SWB. Five single nucleotide polymorphisms (SNPs) were selected from the literature (rs1426371, rs2164273, rs322931, rs3756290, rs490647) and genotyped for genetic association study. We found negative correlations between neuroticism and SWB. On the contrary, extraversion and agreeableness were positively associated with SWB. Three SNPs (rs2164273, rs3756290, rs490647) out of the five were found to connect with personality (extraversion, neuroticism, conscientiousness and openness to experience) and rs490647 variants of GRIK3 was also associated with SWB. Individuals carrying G allele at this site were predisposed to have lower risk to be neuroticism and greater chance to be extraverted, open and satisfied with their life. In summary, our study revealed that rs490647 might be a good candidate genetic variant for personality and SWB in Chinese Han population

MicroRNA: an Emerging Therapeutic Target and Intervention Tool

MicroRNAs (miRNAs) are a class of short non-coding RNAs with posttranscriptional regulatory functions. To date, more than 600 human miRNAs have been experimentally identified, and estimated to regulate more than one third of cellular messenger RNAs. Accumulating evidence has linked the dysregulated expression patterns of miRNAs to a variety of diseases, such as cancer, neurodegenerative diseases, cardiovascular diseases and viral infections. MiRNAs provide its particular layer of network for gene regulation, thus possessing the great potential both as a novel class of therapeutic targets and as a powerful intervention tool. In this regard, synthetic RNAs that contain the binding sites of miRNA have been shown to work as a “decoy” or “miRNA sponge” to inhibit the function of specific miRNAs. On the other hand, miRNA expression vectors have been used to restore or overexpress specific miRNAs to achieve a long-term effect. Further, double-stranded miRNA mimetics for transient replacement have been experimentally validated. Endogenous precursor miRNAs have also been used as scaffolds for the induction of RNA interference. This article reviews the recent progress on this emerging technology as a powerful tool for gene regulation studies and particularly as a rationale strategy for design of therapeutics

Advances in physiologically relevant actuation of shape memory polymers for biomedical applications

The synergistic effects of the combination of hyperthermia and chemotherapy have implicated the critical role of hyperthermia temperatures in clinical practice. Temperature sensitive polymers, which are capable of exhibiting controllable shapes under various temperature actuations, have attracted considerable interests for designing intelligent medical devices. While shape memory performances have been demonstrated with a wide range of temperatures, here we focus our discussion on shape memory polymers with physiologically relevant application temperatures and proper shape recovery speed. This review presents an overview of body-friendly thermo-responsive shape memory polymers, including commonly used biopolymers, various actuation methods, and their potential biomedical applications

Study on the Influential Factors of Noise Characteristics in Dense-Graded Asphalt Mixtures and Field Asphalt Pavements

Determining the influential factors of noise characteristics in dense-graded asphalt mixtures and field asphalt pavement is important in constructing highways that are both low noise and environmentally friendly. In this study, the effects of nominal maximum aggregate size, asphalt binder type, air void percentage, and the service life of pavement on the noise absorption characteristics of asphalt mixtures were first investigated in laboratory. Thereafter, tire/pavement noise measurements were conducted on different types of dense-graded asphalt pavements. The effects of the service lives of the pavements, the types of the pavements, driving speeds, and test temperatures on the noise levels of the pavements were also studied. The Zwicker method is used to calculate psychoacoustic parameters on the tire/pavement noise spectrum. The laboratory results indicate that reducing the nominal maximum aggregate size, using rubber asphalt, and increasing air void percentage as well as surface texture depth improve the sound absorption performance of asphalt mixtures. The field measurements show that laying down asphalt pavements with a shorter service life or larger texture depth, using rubber asphalt, reducing traffic speed, and increasing air temperature can reduce noise

Effect of UV Laser Conditioning on the Structure of KDP Crystal

Multiparametric raster scanning experiments for KDP crystals are carried out to study the laser conditioning efficiency as a function of laser fluence, fluence step, and pulse sequence by using ultraviolet (UV) laser irradiation with pulse duration of approximately 7 ns. It indicates that damage resistance of KDP can be enhanced after conditioning process. And laser conditioning efficiency depends on the maximal fluence which is below the damage threshold. Raman spectra and photothermal absorption have also been studied on KDP crystals before and after multiparametric laser conditioning. Photothermal absorption data reveal that absorbance of conditioned KDP crystal decreases with the increase of laser fluence and the damage threshold of low absorption area is higher. Raman analysis reveals that the effectiveness of laser conditioning relies mainly on the individual mode of PO4 molecule

Contrasting the Performance of Eight Satellite-Based GPP Models in Water-Limited and Temperature-Limited Grassland Ecosystems

Models constitute the primary approaches for predicting terrestrial ecosystem gross primary production (GPP) at regional and global scales. Many satellite-based GPP models have been developed due to the simple algorithms and the low requirements of model inputs. The performances of these models are well documented at the biome level. However, their performances among vegetation subtypes limited by different environmental stresses within a biome remains largely unexplored. Taking grasslands in northern China as an example, we compared the performance of eight satellite-based GPP models, including three light-use efficiency (LUE) models (vegetation photosynthesis model (VPM), modified VPM (MVPM), and moderate resolution imaging spectroradiometer GPP algorithm (MODIS-GPP)) and five statistical models (temperature and greenness model (TG), greenness and radiation model (GR), vegetation index model (VI), alpine vegetation model (AVM), and photosynthetic capacity model (PCM)), between the water-limited temperate steppe and the temperature-limited alpine meadow based on 16 site-year GPP estimates at four eddy covariance (EC) flux towers. The results showed that all the GPP models performed better in the alpine meadow, particularly in the alpine shrub meadow (R-2 0.84), than in the temperate steppe (R-2 0.68). The performance varied greatly among the models in the temperate steppe, while slight intermodel differences existed in the alpine meadow. Overall, MVPM (of the LUE models) and VI (of the statistical models) were the two best-performing models in the temperate steppe due to their better representation of the effect of water stress on vegetation productivity. Additionally, we found that the relatively worse model performances in the temperate steppe were seriously exaggerated by drought events, which may occur more frequently in the future. This study highlights the varying performances of satellite-based GPP models among vegetation subtypes of a biome in different precipitation years and suggests priorities for improving the water stress variables of these models in future efforts