Statistical distribution of HI 21cm intervening absorbers as potential cosmic acceleration probes

Damped Lyman-$\alpha$ Absorber (DLA), or HI 21cm Absorber (H21A), is an important probe to model-independently measure the acceleration of spectroscopic velocity ($v_\mathrm{S}$) via the Sandage-Loeb (SL) effect. Confined by the shortage of DLAs and Background Radio Sources (BRSs) with adequate information, the detectable amount of DLAs is ambiguous in the bulk of previous work. After differing the acceleration of scale factor ($\ddot{a}$) from the first order time derivative of spectroscopic velocity ($\dot{v}_\mathrm{S}$), we make a statistical investigation of the amount of potential DLAs in the most of this paper. Using Kernel Density Estimation (KDE) to depict general redshift distributions of BRSs, observed DLAs and a DLA detection rate with different limitations (1.4GHz flux, HI column density and spin temperature), we provide fitted multi-Gaussian expressions of the three components and their 1$\sigma$ regions by bootstrap, with a proportional constant of H21As in detected DLAs, leading to the measurable number predictions of H21As for FAST, ASKAP and SKA1-Mid in HI absorption blind survey. In our most optimistic condition ($F_\mathrm{1.4GHz}$>10mJy, $N_\mathrm{HI}>2\times10^{20}\mathrm{cm^{-2}}$ and $T_\mathrm{S}$>500K), the FAST, AKSAP and SKA1-Mid would probe about 80, 500 and 600 H21As respectively.Comment: Accepted by MNRAS, 11 pages(without references), 20 figures, 6 table

Polymorphisms of CYP1A1 I462V and GSTM1 genotypes and lung cancer susceptibility in Mongolian

Aim: To study the genotype of cytochrome P450 1A1(CYP1A1) I462V and glutathions S-transferase M1( GSTM1) and the relationship of the genetic polymorphism of them with the susceptibility of lung cancer in Mongolia of China. 

Methods: Allele-specific PCR and a multiplex PCR were employed to identify the genotypes of I462V of CYP1A1 and GSTM1 in a case-control study of 210 lung cancer patients with bronchoscopy diagnosis and 210 matched controls free of malignancy.

Results: The frequencies of the variant CYP1A1(Val/Val) genotypes and GSTM1(-) in lung cancer groups were higher than that in control groups (15.24% vs 7.4% and 56.67% vs 40.95% ). The individuals who carried with CYP1A1(Val/Val) or GSTM1(-) genotype had a significantly higher risk of lung cancer, the OR is 2.56 and 1.89 respectively. Stratified histologically the relative risk increased to 2.6 - fold when the patients carried with two valine alleles than the ones carried one valine allele in cases of SCC. GSTM1(-) genotype is the risk factor of SCC (OR=2.39) and AC(OR=2.16). The presence of at least one Val allele of CYP1A1 and GSTM1(-), the risk of lung cancer was increased, the OR was 4.15 for one Val allele and GSTM1(-) and 2.67 for two Val alleles and GSTM1 Considering ages and smoking status, the risk of lung cancer increased when the age less than 50 who carried with CYP1A1 valine (one or two) alleles or the age during the 51 to 65 who carried with GSTM1(-) genotype. The light smokers with CYP1A1 valine alleles and GSTM1(-) have a high risk for lung cancer. No association was found between the light and heavy drinkers with the susceptibility of lung cancer and the genetic polymorphisms of CYP1A1 I462V and GSTM1(-). 

Conclusion: The valine allele of CYP1A1 was the risk factors of lung cancer especially for SCC and GSTM1(-) also was the risk factor of lung cancer and especially for SCC and AC of Mongolian, China. Light smoking has a influence each other with genotype of CYP1A1 I462V and GSTM1(-) and susceptibility of lung cancer. No relationship was found between the susceptibility of lung cancer and drinkers with genetic polymorphisms of CYP1A1 I462V and GSTM1(-). The influence of genotypes on the susceptibility of lung cancer may depend on the ages. There may be a synergetic interaction between CYP1A1 valine allele and GSTM1(-) genotypes on the elevated susceptibility of lung cancer. So do those genotypes with light smokers. Key words polymorphism; genotype; lung cancer; cytochrome P450；glutathione S-transferase Abbreviations: SCC, squamous cell carcinoma; AC, adenocarcinoma; SCLC, small cell lung cancer; LCLC, large cell lung cance

Entangling Two Bosonic Polaritons via Dispersive Coupling with a Third Mode

We provide a general mechanism of entangling two strongly-coupled bosonic systems that form two hybridized (polariton) modes. This is realized by dispersively coupling with a third bosonic mode. Stationary entanglement is achieved when the two hybridized modes are respectively resonant with the sidebands of the drive field scattered by the third mode and when the weights of the two bosonic modes in the two polaritons are appropriately chosen. The entanglement is robust against dissipations of the system and bath temperature. The entanglement theory is quite general and applicable to a variety of bosonic systems, such as cavity magnomechanical and exciton-photon-phonon systems

Fault Feature Extraction of Bearings for the Petrochemical Industry and Diagnosis Based on High-Value Dimensionless Features

The time and frequency domain features of a petrochemical unit have a variety of effects on the fault type of bearings, and the signal exhibits nonlinearity, unpredictability, and ergodicity. The detection system\u27s important data are disrupted by noise, resulting in a huge number of invalid and partial records. To reduce the influence of these factors on feature extraction, this work presents a method for the fault feature extraction of bearings for the petrochemical industry and for diagnosis based on high-value dimensionless features. Effective data are extracted from the obtained data using a complex data preprocessing approach, and the dimensionless index is expressed. Then, based on the distribution rule of the dimensionless index, the high-value dimensionless features are retrieved. Finally, to ensure sample completeness, a high-value dimensionless feature augmented model is developed. This approach is applied to the bearing fault experiment platform of a petrochemical unit to effectively classify the bearing fault features, which benefits theoretical guidance for the feature extraction of bearings for a petrochemical unit

A peripherally inserted central vein catheter fractured and slid into the right pulmonary artery: A case report

AbstractCatheter fracture is a rare but serious complication of a peripherally inserted central catheter (PICC). An adolescent patient was sent to Tianjin Medical University General Hospital (Tianjin, China) because the PICC was fractured when removed by a nurse. Chest X-ray showed that the PICC fragment slid into the right pulmonary artery. Through emergency surgery, the remainder of the PICC was successfully retrieved by an interventional operation percutaneously via the right femoral vein. PICC fracture is less common and always without significant discomfort if not found timely, and it may lead to serious complications, such as pulmonary embolism, and even death. Thus, nurses, patients and their family members should pay enough attention to the daily maintenance of PICC and have a deep understanding of the reasons associated with PICC fracture as well as how to prevent it. Interventional operation is minimally invasive, which is a good choice for the removal of intravascular foreign bodies, leading to fewer complications and a good prognosis

Self‐Sacrificial Template‐Directed Synthesis of Metal–Organic Framework‐Derived Porous Carbon for Energy‐Storage Devices

Metal–organic framework (MOF)‐derived carbon materials exhibit large surface areas, but dominant micropore characteristics and uncontrollable dimensions. Herein, we propose a self‐sacrificial template‐directed synthesis method to engineer the porous structure and dimensions of MOF‐derived carbon materials. A porous zinc oxide (ZnO) nanosheet solid is selected as the self‐sacrificial template and two‐dimensional (2D) nanostructure‐directing agent to prepare 2D ZIF‐8‐derived carbon nanosheets (ZCNs). The as‐prepared ZCN materials exhibit a large surface area with hierarchical porosity. These intriguing features render ZCN materials advanced electrode materials for electrochemical energy‐storage devices, demonstrating large ion‐accessible surface area and high ion‐/electron‐transport rates. This self‐sacrificial template‐directed synthesis method offers new avenues for rational engineering of the porous structure and dimensions of MOF‐derived porous carbon materials, thus exploiting their full potential for electrochemical energy‐storage devices.On the surface: A self‐sacrificial template‐directed synthesis method is proposed to engineer the porosity and dimensions of MOF‐derived carbon materials. By using a porous nanosheet solid as the self‐sacrificial template and two‐dimensional (2D) nanostructure‐directing agent, 2D ZIF‐8‐derived carbon nanosheets are prepared, which exhibit a large ion‐accessible surface area and rapid ion transport as the electrode materials for electrochemical energy‐storage devices.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137193/1/celc201500536-sup-0001-misc_information.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137193/2/celc201500536.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137193/3/celc201500536_am.pd

Dimethano­lbis[4,4,5,5-tetra­methyl-2-(5-methyl­imidazol-4-yl)-2-imidazoline-1-oxyl-3-oxide-κ2 O,N]cobalt(II) diperchlorate

In the mononuclear title complex, [Co(C11H17N4O2)2(CH3OH)2](ClO4)2, the cobalt(II) atom lies on a symmetry centre and is coordinated by two O,N-bidentate ligands and two trans-arranged O atoms of the methanol mol­ecules in a slightly distorted octa­hedral geometry. In the crystal structure, cations and anions are linked by N—H⋯O and O—H⋯O hydrogen bonds into layers parallel to the bc plane

Effect of ammonia on the immune response of mud crab (Scylla paramamosain) and its susceptibility to mud crab reovirus

Ammonia is one of the major environmental pollutants that affect the growth and physiological functions of organisms. In the present study, the effects of ammonia on the immune response and pathogen resistance of mud crab reovirus (MCRV) in mud crab were investigated. Mud crab were exposed to four different ammonia concentrations (0, 2.5, 5 and 10 mg L-1 ammonia-N) for 7 d. The result showed that aspartate aminotransferase (AST) and alanine aminotransferase (ALT) activity significantly increased after 5 and 10 mg L-1 ammonia exposure. The hepatopancreas superoxide dismutase (SOD), catalase (CAT), and total antioxidative capacity (T-AOC) in ammonia-N group were significantly lower than those in the control group, while the levels of malondialdehyde (MDA) were significantly higher than those in the control group. Significant reductions in total hemocyte counts (THC) were observed after ammonia exposure. After 7d ammonia exposure, mud crabs were injected 100 μL MCRV at 105 copies/g body weight. The mortality of mud crabs in ammonia-N group were significantly higher than those in the control group. All these results suggested that ammonia in water caused a depression in the immune response, and increased susceptibility to MCRV infection

GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning

Molecule property prediction has gained significant attention in recent years. The main bottleneck is the label insufficiency caused by expensive lab experiments. In order to alleviate this issue and to better leverage textual knowledge for tasks, this study investigates the feasibility of employing natural language instructions to accomplish molecule-related tasks in a zero-shot setting. We discover that existing molecule-text models perform poorly in this setting due to inadequate treatment of instructions and limited capacity for graphs. To overcome these issues, we propose GIMLET, which unifies language models for both graph and text data. By adopting generalized position embedding, our model is extended to encode both graph structures and instruction text without additional graph encoding modules. GIMLET also decouples encoding of the graph from tasks instructions in the attention mechanism, enhancing the generalization of graph features across novel tasks. We construct a dataset consisting of more than two thousand molecule tasks with corresponding instructions derived from task descriptions. We pretrain GIMLET on the molecule tasks along with instructions, enabling the model to transfer effectively to a broad range of tasks. Experimental results demonstrate that GIMLET significantly outperforms molecule-text baselines in instruction-based zero-shot learning, even achieving closed results to supervised GNN models on tasks such as toxcast and muv