A Novel and Facile Route to Synthesize Atomic‐Layered MoS2 Film for Large‐Area Electronics

High‐quality and large‐area molybdenum disulfide (MoS₂) thin film is highly desirable for applications in large‐area electronics. However, there remains a challenge in attaining MoS₂ film of reasonable crystallinity due to the absence of appropriate choice and control of precursors, as well as choice of suitable growth substrates. Herein, a novel and facile route is reported for synthesizing few‐layered MoS₂ film with new precursors via chemical vapor deposition. Prior to growth, an aqueous solution of sodium molybdate as the molybdenum precursor is spun onto the growth substrate and dimethyl disulfide as the liquid sulfur precursor is supplied with a bubbling system during growth. To supplement the limiting effect of Mo (sodium molybdate), a supplementary Mo is supplied by dissolving molybdenum hexacarbonyl (Mo(CO)₆) in the liquid sulfur precursor delivered by the bubbler. By precisely controlling the amounts of precursors and hydrogen flow, full coverage of MoS₂ film is readily achievable in 20 min. Large‐area MoS₂ field effect transistors (FETs) fabricated with a conventional photolithography have a carrier mobility as high as 18.9 cm² V^?1 s^?1, which is the highest reported for bottom‐gated MoS₂‐FETs fabricated via photolithography with an on/off ratio of ≈10⁵ at room temperature.     

Effect of stents coated with a combination of sirolimus and alpha-lipoic acid in a porcine coronary restenosis model

The aim of this study was to evaluate antiproliferative sirolimus- and antioxidative alpha-lipoic acid (ALA)-eluting stents using biodegradable polymer [poly-l-lactic acid (PLA)] in a porcine coronary overstretch restenosis model. Forty coronary arteries of 20 pigs were randomized into four groups in which the coronary arteries had a bare metal stent (BMS, n = 10), ALA-eluting stent with PLA (AES, n = 10), sirolimus-eluting stent with PLA (SES, n = 10), or sirolimus- and ALA-eluting stent with PLA (SAS, n = 10). A histopathological analysis was performed 28 days after the stenting. The ALA and sirolimus released slowly over 30 days. There were no significant differences between groups in the injury or inflammation score; however, there were significant differences in the percent area of stenosis (56.2 ± 11.78 % in BMS vs. 51.5 ± 12.20 % in AES vs. 34.7 ± 7.23 % in SES vs. 28.7 ± 7.30 % in SAS, P < 0.0001) and fibrin score [1.0 (range 1.0–1.0) in BMS vs. 1.0 (range 1.0–1.0) in AES vs. 2.0 (range 2.0–2.0) in SES vs. 2.0 (range 2.0–2.0) in SAS, P < 0.0001] between the four groups. The percent area of stenosis based on micro-computed tomography corresponded with the restenosis rates based on histopathological stenosis in different proportions in the four groups (54.8 ± 7.88 % in BMS vs. 50.4 ± 14.87 % in AES vs. 34.5 ± 7.22 % in SES vs. 28.9 ± 7.22 % in SAS, P < 0.05). SAS showed a better neointimal inhibitory effect than BMS, AES, and SES at 1 month after stenting in a porcine coronary restenosis model. Therefore, SAS with PLA can be a useful drug combination for coronary stent coating to suppress neointimal hyperplasia.     

Highly Exposed ?NH2 Edge on Fragmented g-C3N4 Framework with Integrated Molybdenum Atoms for Catalytic CO2 Cycloaddition: DFT and Techno-Economic Assessment

This study focuses on the applicability of single-atom Mo-doped graphitic carbon nitride (GCN) nanosheets which are specifically engineered with high surface area (exfoliated GCN),  NH₂ rich edges, and maximum utilization of isolated atomic Mo for propylene carbonate (PC) production through CO₂ cycloaddition of propylene oxide (PO). Various operational parameters are optimized, for example, temperature (130 °C), pressure (20 bar), catalyst (Mo₂GCN), and catalyst mass (0.1 g). Under optimal conditions, 2% Mo-doped GCN (Mo₂GCN) has the highest catalytic performance, especially the turnover frequency (TOF) obtained, 36.4 h⁻¹ is higher than most reported studies. DFT simulations prove the catalytic performance of Mo₂GCN significantly decreases the activation energy barrier for PO ring-opening from 50–60 to 4.903 kcal mol⁻¹. Coexistence of Lewis acid/base group improves the CO₂ cycloaddition performance by the formation of coordination bond between electron-deficient Mo atom with O atom of PO, while  NH₂ surface group disrupts the stability of CO₂ bond by donating electrons into its low-level empty orbital. Steady-state process simulation of the industrial-scale consumes 4.4 ton h⁻¹ of CO₂ with PC production of 10.2 ton h⁻¹. Techno-economic assessment profit from Mo₂GCN is estimated to be 60.39 million USD year⁻¹ at a catalyst loss rate of 0.01 wt% h⁻¹.     

Periodic orbits: a new language for neuronal dynamics

A new nonlinear dynamical analysis is applied to complex behavior from neuronal systems. The conceptual foundation of this analysis is the abstraction of observed neuronal activities into a dynamical landscape characterized by a hierarchy of "unstable periodic orbits" (UPOs). UPOs are rigorously identified in data sets representative of three different levels of organization in mammalian brain. An analysis based on UPOs affords a novel alternative method of decoding, predicting, and controlling these neuronal systems.     

Detection and characterization of the electron paramagnetic resonance-silent glutathionyl-5,5-dimethyl-1-pyrroline N-oxide adduct derived from redox cycling of phenoxyl radicals in model systems and HL-60 cells

Rapidly growing knowledge about the nature and behaviour of breast cancer has led to many treatment modalities. Consequently, the possibilities of individualizing the treatment of breast cancer increase. The major tool for the determination of an optimal treatment plan is the estimation of the extent of the disease: in other words, staging. As a consequence, together with the expected result of the treatment, the stage of the disease gives information on the prognosis of the patient. Current staging systems insufficiently describe the clinically important features of breast cancer with respect to management and outcome: local and regional extent, invasiveness, aggressiveness, the state of dissemination, and the effectiveness of different treatment modalities. For staging of the local and regional extent, histology plays a prominent role and should be incorporated in future staging systems. Histological workup therefore needs standardisation. Histological parameters as tumour size, grade, nodal status, and vascular invasion are also the most important prognostic factors. Many so-called biological prognostic factors are related to the invasiveness and aggressiveness (metastatic potential) of the tumour, and therefore to the prognosis of the patient. However, these factors do not necessarily predict the effectiveness of certain systemic treatments. Only if the biological foundation of a prognostic factor is completely clarified can treatment be based on this knowledge, and the factor will become a predictor for the treatment effect. Many "biological" prognostic factors do not fulfil this main criterion and are therefore not useful for clinical decision making. A clinically useful staging system covers three primary aims: (1) to guide locoregional treatment, (2) to prognosticate the chance of survival, and (3) to indicate who needs what kind of adjuvant treatment. For the conception of a new staging system the following steps should be taken: standardization of all aspects of histology, identification of regional nodal involvement, and validation of prognostic factors with respect to their predictive value to treatment outcome.     

Hybrid phenol biosensor based on modified phenoloxidase electrode

Electrolytic deposition has been widely used to immobilize biomacromolecules, and it is always the most important factor to preserve or even increase an activity of the immobilized protein. We report here simple and rather universal method for the highly efficient immobilization of laccase for amperometric biosensing. Laccase from Cerrena unicolor has been successfully immobilized (electrolytic deposition) on the surface of thin, ordered polythiophene films (3-methylthiophene/3-thiopheneacetic acid/N-heptyl-3,6-bis(2-thiophene)carbazole). Two different compounds capable of mediating laccase-catalyzed reactions have been tested by cyclic voltammetry. They exhibited quasi-reversible electrodic behaviour with formal redox potentials ranging from 68 and 918 mV (E⁰vs. SCE). The immersion of the laccase-coated electrode in solution with substrate generated large catalytic currents easily recorded by cyclic voltammetry at low potential scan rates. Considering the fact, that immobilization strategy showed high efficiency, obtained results suggest that method for phenoloxidase immobilization has a great potential of enabling high throughput fabrication of bioelectronics’ devices.     

Soft set theory applied to p-ideals of BCI-algebras related to fuzzy points

The notions of $(\overline{\in}, \overline{\in} \vee \overline{\hbox{q}})The notions of ([`( ? )],[`( ? )] ú[`q])(\overline{\in}, \overline{\in} \vee \overline{\hbox{q}})-fuzzy p-ideals and fuzzy p-ideals with thresholds related to soft set theory are discussed. Relations between ([`( ? )],[`( ? )] ú[`q])(\overline{\in}, \overline{\in} \vee \overline{\hbox{q}})-fuzzy ideals and ([`( ? )],[`( ? )] ú[`q])(\overline{\in}, \overline{\in} \vee \overline{\hbox{q}})-fuzzy p-ideals are investigated. Characterizations of an ([`( ? )],[`( ? )] ú[`q])(\overline{\in}, \overline{\in} \vee \overline{\hbox{q}})-fuzzy p-ideal and a fuzzy p-ideal with thresholds are displayed. Implication-based fuzzy p-ideals are discussed.     

Robust portfolio optimization via solution to the Hamilton–Jacobi–Bellman equation

We consider a problem of dynamic stochastic portfolio optimization modelled by a fully non-linear Hamilton–Jacobi–Bellman (HJB) equation. Using the Riccati transformation, the HJB equation is transformed to a simpler quasi-linear partial differential equation. An auxiliary quadratic programming problem is obtained, which involves a vector of expected asset returns and a covariance matrix of the returns as input parameters. Since this problem can be sensitive to the input data, we modify the problem from fixed input parameters to worst-case optimization over convex or discrete uncertainty sets both for asset mean returns and their covariance matrix. Qualitative as well as quantitative properties of the value function are analysed along with providing illustrative numerical examples. We show application to robust portfolio optimization for the German DAX30 Index.     

Sparse and Truncated Nuclear Norm Based Tensor Completion

One of the main difficulties in tensor completion is the calculation of the tensor rank. Recently a tensor nuclear norm, which is equal to the weighted sum of matrix nuclear norms of all unfoldings of the tensor, was proposed to address this issue. However, in this approach, all the singular values are minimized simultaneously. Hence the tensor rank may not be well approximated. In addition, many existing algorithms ignore the structural information of the tensor. This paper presents a tensor completion algorithm based on the proposed tensor truncated nuclear norm, which is superior to the traditional tensor nuclear norm. Furthermore, to maintain the structural information, a sparse regularization term, defined in the transform domain, is added into the objective function. Experimental results showed that our proposed algorithm outperforms several state-of-the-art tensor completion schemes.