Anisotropic Growth of Nonlayered CdS on MoS<inf>2</inf> Monolayer for Functional Vertical Heterostructures

Two dimensional (2D) semiconductors have emerged as a crucial material for use in next generation optotelectronics. Similar to micro-electronic devices, 2D vertical heterostructures would most likely be the elemental components for future nanoscale electronics and optotelectronics. To date, the components of mostly reported 2D van der Waals heterostructures are restricted to layer crystals. In this communication, we demonstrate that non-layered semiconductors of CdS can be epitaxially grown on to 2D layered MoS2 substrate to form a new quasi vertical heterostructure with clean interface by chemical vapor deposition. Photodetectors based on this CdS/MoS2 heterostructure show broader wavelength response and ~50 fold improvement in photoresponsivity, compared to the devices fabricated from MoS2 monolayer only. This research opens up a way to fabricate a variety of functional quasi heterostructures from non-layer semiconductors.This work is supported by the National Natural Science Foundation of China (NSFC, No.61172001, 21373068, 21303030), the National key Basic Research Program of China (973 Program) under Grant No. 2013CB632900. TH acknowledges from a Royal Academy of Engineering Research Fellowship (Graphlex).This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/adfm.20150477

Serum Secreted Protein Acidic and Rich in Cysteine-Like 1 as a Biochemical Predictor for Prognosticating Clinical Outcomes After Acute Supratentorial Intracerebral Hemorrhage: A Prospective Cohort Study [Corrigendum]

Huang J, Shao F, Chen B, Zheng G, Shen J, Qiu S. Neuropsychiatr Dis Treat. 2023;19:2709&#x2013;2728. The authors have advised that the funding statement on page 2727 is incorrect. The text &#x201C;(No. 202107071918000249496)&#x201D; should read &#x201C;(No. 20201203B59)&#x201D;. The authors apologize for this error

Scaling and Memory Effect in Volatility Return Interval of the Chinese Stock Market

We investigate the probability distribution of the volatility return intervals $\tau$ for the Chinese stock market. We rescale both the probability distribution $P_{q}(\tau)$ and the volatility return intervals $\tau$ as $P_{q}(\tau)=1/\bar{\tau} f(\tau/\bar{\tau})$ to obtain a uniform scaling curve for different threshold value $q$. The scaling curve can be well fitted by the stretched exponential function $f(x) \sim e^{-\alpha x^{\gamma}}$, which suggests memory exists in $\tau$. To demonstrate the memory effect, we investigate the conditional probability distribution $P_{q} (\tau|\tau_{0})$, the mean conditional interval $$ and the cumulative probability distribution of the cluster size of $\tau$. The results show clear clustering effect. We further investigate the persistence probability distribution $P_{\pm}(t)$ and find that $P_{-}(t)$ decays by a power law with the exponent far different from the value 0.5 for the random walk, which further confirms long memory exists in $\tau$. The scaling and long memory effect of $\tau$ for the Chinese stock market are similar to those obtained from the United States and the Japanese financial markets.Comment: 10 elsart pages including 7 eps figure

An end-to-end deep learning histochemical scoring system for breast cancer TMA

One of the methods for stratifying different molecular classes of breast cancer is the Nottingham Prognostic Index Plus (NPI+) which uses breast cancer relevant biomarkers to stain tumour tissues prepared on tissue microarray (TMA). To determine the molecular class of the tumour, pathologists will have to manually mark the nuclei activity biomarkers through a microscope and use a semi-quantitative assessment method to assign a histochemical score (H-Score) to each TMA core. Manually marking positively stained nuclei is a time consuming, imprecise and subjective process which will lead to inter-observer and intra-observer discrepancies. In this paper, we present an end-to-end deep learning system which directly predicts the H-Score automatically. Our system imitates the pathologists’ decision process and uses one fully convolutional network (FCN) to extract all nuclei region (tumour and non-tumour), a second FCN to extract tumour nuclei region, and a multi-column convolutional neural network which takes the outputs of the first two FCNs and the stain intensity description image as input and acts as the high-level decision making mechanism to directly output the H-Score of the input TMA image. To the best of our knowledge, this is the first end-to-end system that takes a TMA image as input and directly outputs a clinical score. We will present experimental results which demonstrate that the H-Scores predicted by our model have very high and statistically significant correlation with experienced pathologists’ scores and that the H-Score discrepancy between our algorithm and the pathologists is on par with the inter-subject discrepancy between the pathologists

Growth and characterization of A_{1-x}K_xFe_2As_2 (A = Ba, Sr) single crystals with x=0 - 0.4

Single crystals of A$_{1-x}$K$_x$Fe$_2$As$_2$ (A=Ba, Sr) with high quality have been grown successfully by FeAs self-flux method. The samples have sizes up to 4 mm with flat and shiny surfaces. The X-ray diffraction patterns suggest that they have high crystalline quality and c-axis orientation. The non-superconducting crystals show a spin-density-wave (SDW) instability at about 173 K and 135 K for Sr-based and Ba-based compound, respectively. After doping K as the hole dopant into the BaFe$_2$As$_2$ system, the SDW transition is smeared, and superconducting samples with the compound of Ba$_{1-x}$K$_x$Fe$_2$As$_2$ (0 $< x \leqslant$ 0.4) are obtained. The superconductors characterized by AC susceptibility and resistivity measurements exhibit very sharp superconducting transition at about 36 K, 32 K, 27 K and 23 K for x= 0.40,0.28,0.25 and 0.23, respectively.Comment: 9 pages, 6 figures, 1 table. This paper together with new data are modified into a new pape

Human Equilibrative Nucleoside Transporter 1: Novel Biomarker and Prognostic Indicator for Patients with Gemcitabine-Treated Pancreatic Cancer

Jianchun Xiao,1,&ast; Fangyu Zhao,1,&ast; Wenhao Luo,1,&ast; Gang Yang,1 Yicheng Wang,1 Jiangdong Qiu,1 Yueze Liu,1 Lei You,1 Lianfang Zheng,2 Taiping Zhang1,3 1Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, People’s Republic of China; 2Department of Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, People’s Republic of China; 3Clinical Immunology Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Taiping Zhang, Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, People’s Republic of China, Email [email protected]: This article aimed to find appropriate pancreatic cancer (PC) patients to treat with Gemcitabine with better survival outcomes by detecting hENT1 levels.Methods: We collected surgical pathological tissues from PC patients who received radical surgery in our hospital from September 2004 to December 2014. A total of 375 PC tissues and paired adjacent nontumor tissues were employed for the construction of 4 tissue microarrays (TMAs). The quality of the 4 TMAs was examined by HE staining. We performed immunohistochemistry analysis to evaluate hENT1 expression in the TMAs. Moreover, we detected hENT1 expression level and proved the role of hENT1 in cell proliferation, drug resistance, migration and invasion in vivo and vitro.Results: The results indicated that low hENT1 expression indicated a significantly poor outcome in PC patients, including shortened DFS (21.6± 2.8 months versus 36.9± 4.0 months, p 467 U/mL (37.9± 4.1 versus 22.9± 4.0, p=0.04). In the subgroup analysis, a high hENT1 expression level was related to a longer OS(39.4± 4.0 versus 31.5± 3.9, p=0.001) and DFS(35.7± 4.0 versus 20.6± 2.7; p< 0.0001) in the Gemcitabine subgroup.Conclusion: PC patients with high hENT1 expression have a better survival outcomes when receiving Gemcitabine. hENT1 expression can be a great prognostic indicator for PC patients to receive Gemcitabine treatment.Keywords: pancreatic cancer, human equilibrative nucleoside transporter 1, hENT1, gemcitabine chemoresistance, prognostic indicator, survival improvemen

Measurement of \psip Radiative Decays

Using 14 million psi(2S) events accumulated at the BESII detector, we report first measurements of branching fractions or upper limits for psi(2S) decays into gamma ppbar, gamma 2(pi^+pi^-), gamma K_s K^-pi^++c.c., gamma K^+ K^- pi^+pi^-, gamma K^{*0} K^- pi^+ +c.c., gamma K^{*0}\bar K^{*0}, gamma pi^+pi^- p pbar, gamma 2(K^+K^-), gamma 3(pi^+pi^-), and gamma 2(pi^+pi^-)K^+K^- with the invariant mass of hadrons below 2.9GeV/c^2. We also report branching fractions of psi(2S) decays into 2(pi^+pi^-) pi^0, omega pi^+pi^-, omega f_2(1270), b_1^\pm pi^\mp, and pi^0 2(pi^+pi^-) K^+K^-.Comment: 5 pages, 4 figure

A Unified Approach to the Classical Statistical Analysis of Small Signals

We give a classical confidence belt construction which unifies the treatment of upper confidence limits for null results and two-sided confidence intervals for non-null results. The unified treatment solves a problem (apparently not previously recognized) that the choice of upper limit or two-sided intervals leads to intervals which are not confidence intervals if the choice is based on the data. We apply the construction to two related problems which have recently been a battle-ground between classical and Bayesian statistics: Poisson processes with background, and Gaussian errors with a bounded physical region. In contrast with the usual classical construction for upper limits, our construction avoids unphysical confidence intervals. In contrast with some popular Bayesian intervals, our intervals eliminate conservatism (frequentist coverage greater than the stated confidence) in the Gaussian case and reduce it to a level dictated by discreteness in the Poisson case. We generalize the method in order to apply it to analysis of experiments searching for neutrino oscillations. We show that this technique both gives correct coverage and is powerful, while other classical techniques that have been used by neutrino oscillation search experiments fail one or both of these criteria.Comment: 40 pages, 15 figures. Changes 15-Dec-99 to agree more closely with published version. A few small changes, plus the two substantive changes we made in proof back in 1998: 1) The definition of "sensitivity" in Sec. V(C). It was inconsistent with our actual definition in Sec. VI. 2) "Note added in proof" at end of the Conclusio