Phylogeographic Structure of a Tethyan Relict Capparis spinosa

Complex geological movements more or less affected or changed floristic structures, while the alternation of glacials and interglacials is presumed to have further shaped the present discontinuous genetic pattern of temperate plants. Here we consider Capparis spinosa, a xeromorphic Tethyan relict, to discuss its divergence pattern and explore how it responded in a stepwise fashion to Pleistocene geologic and climatic changes. 267 individuals from 31 populations were sampled and 24 haplotypes were identified, based on three cpDNA fragments (trnL-trnF, rps12-rpl20, and ndhF). SAMOVA clustered the 31 populations into 5 major clades. AMOVA suggests that gene flow between them might be restricted by vicariance. Molecular clock dating indicates that intraspecific divergence began in early Pleistocene, consistent with a time of intense uplift of the Himalaya and Tianshan Mountains, and intensified in mid-Pleistocene. Species distribution modeling suggests range reduction in the high mountains during the Last Glacial Maximum (LGM) as a result of cold climates when glacier advanced, while gorges at midelevations in Tianshan appear to have served as refugia. Populations of low-altitude desert regions, on the other hand, probably experienced only marginal impacts from glaciation, according to the high levels of genetic diversity

Spatial-temporal characteristics and driving factors of carbon emissions from the construction industry in the Belt and Road region of China

To promote sustainable economic development in the Belt and Road region of China, reducing carbon emissions is essential. The construction industry is a major contributor to carbon emissions in China. Therefore, studying the dynamic evolution of carbon emissions from the construction industry in this region and its driving factors is of great significance for effectively controlling emissions and achieving China’s carbon peak and carbon neutrality targets. This paper first employs the Slope model, Moran’s I index, and standard deviation ellipse to reveal the spatial-temporal characteristics of carbon emissions from the construction industry, and then applies the geographical detector model to identify the main driving factors of carbon emissions. The results indicate that: (1) From 2006 to 2021, the total carbon emissions showed a fluctuating growth trend, and there were significant differences in emissions among different regions. (2) Carbon emissions in most provinces exhibited a moderate growth trend, and there was significant spatial correlation and aggregation of inter-provincial emissions. Regional carbon emissions from 2006 to 2021 showed a spatial distribution pattern from northeast to southwest, with a weakening trend, and the center of gravity mainly distributed in the east of the region. (3) Labor input, urbanization rate, total output value of the construction industry, degree of opening up, and energy intensity are the main factors influencing the spatial heterogeneity of carbon emissions from the construction industry, and the majority of the interaction types between factors were bivariate enhancement. This study aims to provide theoretical support for policymakers to formulate appropriate policies for building energy conservation and emission reduction

LLM-FuncMapper: Function Identification for Interpreting Complex Clauses in Building Codes via LLM

As a vital stage of automated rule checking (ARC), rule interpretation of regulatory texts requires considerable effort. However, interpreting regulatory clauses with implicit properties or complex computational logic is still challenging due to the lack of domain knowledge and limited expressibility of conventional logic representations. Thus, LLM-FuncMapper, an approach to identifying predefined functions needed to interpret various regulatory clauses based on the large language model (LLM), is proposed. First, by systematically analysis of building codes, a series of atomic functions are defined to capture shared computational logics of implicit properties and complex constraints, creating a database of common blocks for interpreting regulatory clauses. Then, a prompt template with the chain of thought is developed and further enhanced with a classification-based tuning strategy, to enable common LLMs for effective function identification. Finally, the proposed approach is validated with statistical analysis, experiments, and proof of concept. Statistical analysis reveals a long-tail distribution and high expressibility of the developed function database, with which almost 100% of computer-processible clauses can be interpreted and represented as computer-executable codes. Experiments show that LLM-FuncMapper achieve promising results in identifying relevant predefined functions for rule interpretation. Further proof of concept in automated rule interpretation also demonstrates the possibility of LLM-FuncMapper in interpreting complex regulatory clauses. To the best of our knowledge, this study is the first attempt to introduce LLM for understanding and interpreting complex regulatory clauses, which may shed light on further adoption of LLM in the construction domain

Quasi-1D graphene superlattices formed on high index surfaces

We report preparation of large area quasi-1D monolayer graphene superlattices on a prototypical high index surface Cu(410)-O and characterization by Raman spectroscopy, Auger electron spectroscopy (AES), low energy electron diffraction (LEED), scanning tunneling microscopy (STM) and scanning tunneling spectroscopy (STS). The periodically stepped substrate gives a 1D modulation to graphene, forming a superlattice of the same super-periodicity. Consequently the moire pattern is also quasi-1D, with a different periodicity. Scanning tunneling spectroscopy measurements revealed new Dirac points formed at the superlattice Brillouin zone boundary as predicted by theories.Comment: 4 figure

Preparation of N- TiO

This study applied the microwave/sol-gel method to prepare nitrogen-doped TiO2 (N-TiO2). The N-TiO2 was immobilized in glass balls to form N-TiO2/glass beads and applied to degrade Bisphenol A (BPA) under visible-light and sunlight irradiation. The characteristics of the prepared photocatalysts were analyzed by X-ray diffraction (XRD), UV-Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). Experimental results demonstrate that the percentage of anatase increased as the amount of N in N-TiO2 increased. Compared with the undoped TiO2 (420 nm), spectra show that the absorption edge shifted to a longer wavelength (445 nm) after N doping. The XPS characterization confirms the substitution of crystal lattice O to N species in N-TiO2, forming Ti–O–N and N–Ti–O. With an increased N/Ti ratio, photodegradation efficiency increased and then decreased; moreover, the optimal amount for N doping was determined as an N/Ti mole ratio of 0.08 (0.1 NT). The efficiency of 0.1 NT in doing BPA photodegradation was greater than that of Degussa P25. After reaction for 61 min, the mineralization percentage of 0.1 NT under visible-light irradiation reached 41%. Photocatalyst efficiency decreased as the number of repeats increased in the visible-light/N-TiO2 system; however, these systems were stable during reaction

A radiomics-based study of deep medullary veins in infants: Evaluation of neonatal brain injury with hypoxic-ischemic encephalopathy via susceptibility-weighted imaging

ObjectiveThe deep medullary veins (DMVs) can be evaluated using susceptibility-weighted imaging (SWI). This study aimed to apply radiomic analysis of the DMVs to evaluate brain injury in neonatal patients with hypoxic-ischemic encephalopathy (HIE) using SWI.MethodsThis study included brain magnetic resonance imaging of 190 infants with HIE and 89 controls. All neonates were born at full-term (37+ weeks gestation). To include the DMVs in the regions of interest, manual drawings were performed. A Rad-score was constructed using least absolute shrinkage and selection operator (LASSO) regression to identify the optimal radiomic features. Nomograms were constructed by combining the Rad-score with a clinically independent factor. Receiver operating characteristic curve analysis was applied to evaluate the performance of the different models. Clinical utility was evaluated using a decision curve analysis.ResultsThe combined nomogram model incorporating the Rad-score and clinical independent predictors, was better in predicting HIE (in the training cohort, the area under the curve was 0.97, and in the validation cohort, it was 0.95) and the neurologic outcomes after hypoxic-ischemic (in the training cohort, the area under the curve was 0.91, and in the validation cohort, it was 0.88).ConclusionBased on radiomic signatures and clinical indicators, we developed a combined nomogram model for evaluating neonatal brain injury associated with perinatal asphyxia