Tuning the electronic and magnetic properties of metal-doped phenanthrene by codoping method

By first principles method, we have determined the geometric configuration of K/Ba-codoped phenanthrene based on the formation energy calculations, and systematically investigated its electronic and magnetic properties. There are two bands crossing Fermi energy which mainly result from the LUMO+1 orbitals of two phenanthrene molecules in a unit cell, and the cylinder-like Fermi surface along the ${\Gamma}$-Z direction reflects the two-dimension character of metallic conduction of K/Ba-codoped phenanthrene. Compared to K-doped phenanthrene, K/Ba-codoping can donate more electrons to molecule to modify the electronic structure, while the intercalation of dopants does not result in the large distortion of molecule. (KBa)$_1$phenanthrene is a magnetic metal with the spin moment of 0.32 ${\mu}_B$ per each molecule, and unexpectedly, the spins gather in one edge of molecule rather than a uniform distribution on the whole molecule. Our results demonstrate that codoping of monovalent and bivalent metals is an effective approach to modulate the electronic properties of metal-doped hydrocarbons.Comment: 6 pages, 5 figure

High-speed rail to prosperity? Assessing the role of transportation improvement in the urban economy

Investigate the impact of high-speed rail (HSR) on local economy is of great importance and interest to policy makers and scholars. Though there is a big body of literature in this area, the estimates of such impact are inconsistent or even contradictory. The empirical evidence remains problematic for several reasons: endogenous route placement; omitted variable bias; heterogeneity across different regions; various confounding factors. In this paper, we assess this impact by constructing the appropriate counterfactual in the absence of HSR services with similar GDP level and GDP trend before the debut of HSR services. The control group forms a good fit for the treatment group, and the economic performance of the control group was even slightly stronger than that of the treatment group before 2007. Using the DID method, we find the HSR network promoted local GDP by approximately 3.3 percentage points. The introduction of HSR service helped cities attract more industrial enterprises and achieve more industrial output, but its effect on the service sector was not pronounced. Our results are robust to different sample selection procedures, to the dynamic analyses, to different empirical strategies. Our study thus provides new and solid empirical support to the argument that HSR benefits local economic development

Surgical Management of Urolithiasis in Patients After Urinary Diversion

Objective: To present our experience in surgical management of urolithiasis in patients after urinary diversion. Patients and Methods: Twenty patients with urolithiasis after urinary diversion received intervention. Percutaneous nephrolithotomy, percutaneous based antegrade ureteroscopy with semi-rigid or flexible ureteroscope, transurethral reservoir lithotripsy, percutaneous pouch lithotripsy and open operation were performed in 8, 3, 2, 6, and 1 patients, respectively. The operative finding and complications were retrospectively collected and analyzed. Results: The mean stone size was 4.5±3.1 (range 1.5-11.2) cm. The mean operation time was 82.0±11.5 (range 55-120) min. Eighteen patients were rendered stone free with a clearance of 90%. Complications occurred in 3 patients (15%). Two patients (10%) had postoperative fever greater than 38.5°C, and one patient (5%) suffered urine extravasations from percutaneous tract. Conclusions: The percutaneous based procedures, including percutaneous nephrolithotomy, antegrade ureteroscopy with semi-rigid ureteroscope or flexible ureteroscope from percutaneous tract, and percutaneous pouch lithotripsy, provides a direct and safe access to the target stones in patients after urinary diversion, and with high stone free rate and minor complications. The surgical management of urolithiasis in patients after urinary diversion requires comprehensive evaluation and individualized consideration depending upon the urinary diversion type, stone location, stone burden, available resource and surgeon experience

Microorganism-decorated nanocellulose for efficient diuron removal

The environmental impacts of diuron have generated growing interest in remediation methods to prevent the potential threat of diuron to ecosystem integrity and human beings. Here, a simple and effective nanocellulose-based biocomposite coupled with Arthrobacter globiformis D47 as a herbicide degrader is presented for the rapid elimination of diuron. First, bacterium D47 was immobilized on the fiber networks of the nanocellulose, forming a bacteria-decorated nanocellulose (BDN) that outperformed direct utilization of bacterial suspensions for diuron decomposition. More importantly, the advantageous features of BDN could remarkably broaden its applicability since the bio-hybrid material rapidly degraded diuron and its major metabolite 3,4-dichloroaniline at low concentrations (1-10 mg ⁻¹). In addition, the morphology of BDN revealed the excellent biocompatibility of nanocellulose as cell scaffolding for bacterial proliferation. Then, the adsorption capacity of the nanocellulose and the enzymatic metabolism of the bacteria were validated as a joint mechanism of the BDN biocomposites in the removal of diuron. In addition, the wide applicability of BDN was further verified by the degradation of diuron in environmental matrices and other phenylurea herbicide targets. Therefore, the novel microorganism-immobilized nanocellulose composites provide a promising alternative material combining functional microorganisms with emerging nanomaterials, which may facilitate the bioremediation of organic xenobiotic pollution in complex environments

Genetic marker anchoring by six-dimensional pools for development of a soybean physical map

<p>Abstract</p> <p>Background</p> <p>Integrated genetic and physical maps are extremely valuable for genomic studies and as important references for assembling whole genome shotgun sequences. Screening of a BAC library using molecular markers is an indispensable procedure for integration of both physical and genetic maps of a genome. Molecular markers provide anchor points for integration of genetic and physical maps and also validate BAC contigs assembled based solely on BAC fingerprints. We employed a six-dimensional BAC pooling strategy and an <it>in silico </it>approach to anchor molecular markers onto the soybean physical map.</p> <p>Results</p> <p>A total of 1,470 markers (580 SSRs and 890 STSs) were anchored by PCR on a subset of a Williams 82 <it>Bst</it>Y I BAC library pooled into 208 pools in six dimensions. This resulted in 7,463 clones (~1× genome equivalent) associated with 1470 markers, of which the majority of clones (6,157, 82.5%) were anchored by one marker and 1106 (17.5%) individual clones contained two or more markers. This contributed to 1184 contigs having anchor points through this 6-D pool screening effort. In parallel, the 21,700 soybean Unigene set from NCBI was used to perform <it>in silico </it>mapping on 80,700 Williams 82 BAC end sequences (BES). This <it>in silico </it>analysis yielded 9,835 positive results anchored by 4152 unigenes that contributed to 1305 contigs and 1624 singletons. Among the 1305 contigs, 305 have not been previously anchored by PCR. Therefore, 1489 (78.8%) of 1893 contigs are anchored with molecular markers. These results are being integrated with BAC fingerprints to assemble the BAC contigs. Ultimately, these efforts will lead to an integrated physical and genetic map resource.</p> <p>Conclusion</p> <p>We demonstrated that the six-dimensional soybean BAC pools can be efficiently used to anchor markers to soybean BACs despite the complexity of the soybean genome. In addition to anchoring markers, the 6-D pooling method was also effective for targeting BAC clones for investigating gene families and duplicated regions in the genome, as well as for extending physical map contigs.</p

End-to-End Insulator String Defect Detection in a Complex Background Based on a Deep Learning Model

Normal power line insulators ensure the safe transmission of electricity. The defects of the insulator reduce the insulation, which may lead to the failure of power transmission systems. As unmanned aerial vehicles (UAVs) have developed rapidly, it is possible for workers to take and upload aerial images of insulators. Proposing a technology to detect insulator defects with high accuracy in a short time can be of great value. The existing methods suffer from complex backgrounds so that they have to locate and extract the insulators at first. Some of them make detection relative to some specific conditions such as angle, brightness, and object scale. This study aims to make end-to-end detections using aerial images of insulators, giving the locations of insulators and defects at the same time while overcoming the disadvantages mentioned above. A DEtection TRansformer (DETR) having an encoder–decoder architecture adopts convolutional neural network (CNN) as the backbone network, applies a self-attention mechanism for computing, and utilizes object queries instead of a hand-crafted process to give the direct predictions. We modified this for insulator detection in complex aerial images. Based on the dataset we constructed, our model can get 97.97 in mean average precision when setting the threshold of intersection over union at 0.5, which is better than Cascade R-CNN and YOLOv5. The inference speed of our model can reach 25 frames per second, which is qualified for actual use. Experimental results demonstrate that our model meets the robustness and accuracy requirements for insulator defect detection