On Suborbital Graphs for the Extended Modular Group {\hat{\Gamma}}

In this paper, we show that the extended modular group ${\hat{\Gamma}}$ acts on ${\hat{\mathbb{Q}}}$ transitively and imprimitively. Then the number of orbits of ${\hat{\Gamma} _{0}(N)}$ on ${\hat{\mathbb{Q}}}$ is calculated and compared with the number of orbits of ${\Gamma _{0}(N)}$ on ${\hat{\mathbb{Q}}}$ . Especially, we obtain the graphs ${\hat{G}_{u, N}}$ of ${\hat{\Gamma}_{0}(N)}$ on ${\hat{\mathbb{Q}}}$ , for each ${N\in\mathbb{N}}$ and each unit ${u \in U_{N} }$ , then we determine the suborbital graph ${\hat{F}_{u,N}}$ . We also give the edge conditions in ${\hat{G}_{u, N}}$ and the necessary and sufficient conditions for a circuit to be triangle in ${\hat{F}_{u, N}.}$      

An approximation to the cross sections of Z l boson production at CLIC by using neural networks

In this work, the possible dynamics associated with leptophilic Z _l boson at CLIC (Compact Linear Collider) have been investigated by using artificial neural networks (ANNs). These hypotetic massive boson Z _l have been shown through the process e ⁺ e ^?→µ⁺µ^?. Furthermore, the invariant mass distributions for final muons have been consistently predicted by using ANN. For these highly non-linear data, we have constructed consistent empirical physical formulas (EPFs) by appropriate feed-forward ANN. These ANNEPFs can be used to derive further physical functions which could be relevant to studying Z _l .     

On the lifetime behavior of a discrete time shock model

In this article, we study a shock model in which the shocks occur according to a binomial process, i.e. the interarrival times between successive shocks follow a geometric distribution with mean 1/p$1/p$. According to the model, the system fails when the time between two consecutive shocks is less than a prespecified level. This is the discrete time version of the so-called δ$\delta$-shock model which has been previously studied for the continuous case. We obtain the probability mass function and probability generating function of the system’s lifetime. We also present an extension of the results to the case where the shock occurrences are dependent in a Markovian fashion.     

Chiral Aggregates of Triphenylamine‐Based Dyes for Depleting the Production of Hydrogen Peroxide in the Photochemical Water‐Splitting Process

Recent studies on water‐splitting photoelectrochemical cells (PECs) have demonstrated the intriguing possibility of controlling the spin state in this chemical reaction to form H₂ and O₂ by exploiting the chirality of organic π‐conjugated supramolecular polymers. Although this fascinating phenomenon has been disclosed, the chiral supramolecular materials reported thus far are not optimized for acting as efficient photosensitizer for dye‐sensitized PECs. In this work we report on the design, synthesis, and characterization of chiral supramolecular aggregates based on C₃‐symmetric triphenylamine‐based dyes that are able to both absorb visible light and control the spin state of the process. Variable temperature‐dependent spectroscopic measurements reveal the assembly process of the dyes and confirm the formation of chiral aggregates, both in solution as well as on solid supports. Photoelectrochemical measurements on TiO₂‐based anodes validate the advantage of using chiral supramolecular aggregates as photosensitizer displaying higher photocurrent compared to achiral analogues. Moreover, fluorimetric tests for the quantification of the hydrogen peroxide produced, confirm the possibility of controlling the spin of the reaction exerting spin‐selection with chiral supramolecular polymers. These results represent a further step towards the next‐generation of organic‐based water‐splitting solar cells.     

Minimization of Interferences in Flow Injection Amperometric Glucose Biosensor Based on Oxidation of Enzymatically‐produced H2O2

One of the major problems in amperometric biosensors based on detection of H₂O₂ produced by enzymatic reaction between oxidase enzymes and substrate is the interference of redox active compounds such as ascorbic acid (AA), dopamine (DA) and uric acid (UA). To minimize these interferences, sodium bismuthate was used for the first time as an insoluble pre‐oxidant in the flow injection (FI) amperometric glucose biosensor at a Glucose oxidase (GOx) immobilized Pt/Pd bimetallic modified pre‐anodized pencil graphite electrode (p.PGE). In this context, these interfering compounds were injected into a flow injection analysis (FIA) system using an injector which was filled with NaBiO₃. Thus, these interferents were converted into their redox inactive oxidized forms before reaching the electrode in the flow cell. While glucose was not influenced by the pre‐oxidant in the injector, the huge oxidation peak currents of the interferents decreased significantly in the biosensor. FI amperometric current time curves showed that the AA, DA and UA were minimized by 96 %, 86 %, and 98 % respectively, in the presence of an equivalent concentration of interferences in a 1.0 mM glucose solution. The proposed FI amperometric glucose biosensor exhibits a wide linear range (0.01–10 mM, R²=0.9994) with a detection limit of 2.4×10^?3 mM. Glucose levels in the artificial serum and two real samples were successfully determined using the fabricated FI amperometric biosensor.     

Double-exchange model for molecule-based magnets

We report a detailed study of a double-exchange model proposed for the molecule-based magnets. The model is applied to a two-dimensional periodic complex made of a transition metal and an organic molecule in which the electronic structure is described by effective d orbitals of the transition metal ion at infinite Hund's coupling limit and the lowest unoccupied molecular orbital of the organic molecule, π^∗. Depending on the average electron density of the organic molecules and various superexchange couplings between metal ions' core spins, magnetic states of the complex are investigated. Performing Monte Carlo calculations on a model Hamiltonian for various electron densities of the organic molecule, the average magnetization and critical magnetic ordering temperatures are determined.     

Enhanced Performance of Organic/Inorganic Hybrid Nanomaterials bearing Impregnated [PdL2] Complexes as Counter‐Electrode Catalyst for Dye‐Sensitized Solar Cells

N‐coordinate Pd²⁺ complexes [PdL₂] (L: N‐N‐quinoline‐8‐yl‐R‐benzenesulfonamides) ( 6–10 ) and [PdL₂] complexes assembled on multi‐wall carbon nanotubes (MWCNTs) hybrid nanomaterials were fabricated and characterized by various techniques. The [PdL₂] impregnated MWCNTs materials ( 11–15 ) were applied as a counter electrode (CE) catalyst for triiodide to iodide reduction reaction in the dye‐sensitized solar cells (DSSC) and investigated electro‐catalytic activities. The MWCNTs‐supported [PdL₂] CEs ( 11–15 ) are exhibits as Pt‐free CE with good power conversion efficiencies (PCEs), and compared to platinum and bare MWCNTs CEs and the PCE of bare MWCNTs was clearly improved by means of [PdL₂] complexes ( 6–10 ). The DSSCs based on the hybrid counter electrodes (CEs) ( 11–15 ) and bare MWCNTs are indicated a relative efficiency ( ? _rel ) of 64.27%, 54.07%, 53.75%, 51.52% 44.82% and 27.27% concerning a Pt CE control device set at 100%. The report emphasizes that [PdL₂] impregnated MWCNTs type counter electrodes (CEs) ( 11–15 ) are promising as effectively catalyst in working device design, particularly taking into account the eco‐friendly approach of the hybrids.     

Optimal learning for sequential sampling with non-parametric beliefs

We propose a sequential learning policy for ranking and selection problems, where we use a non-parametric procedure for estimating the value of a policy. Our estimation approach aggregates over a set of kernel functions in order to achieve a more consistent estimator. Each element in the kernel estimation set uses a different bandwidth to achieve better aggregation. The final estimate uses a weighting scheme with the inverse mean square errors of the kernel estimators as weights. This weighting scheme is shown to be optimal under independent kernel estimators. For choosing the measurement, we employ the knowledge gradient policy that relies on predictive distributions to calculate the optimal sampling point. Our method allows a setting where the beliefs are expected to be correlated but the correlation structure is unknown beforehand. Moreover, the proposed policy is shown to be asymptotically optimal.     

Addition of trifluoromethyltrimethylsilane to acyl phosphonates: synthesis of TMS-protected 1-alkyl-1-trifluoromethyl-1-hydroxyphosphonates and 1-aryldifluoroethenyl phosphates

Addition reactions of nucleophilic CF3TMS to acyl phosphonates were investigated. Various acyl phosphonates reacted readily with CF3TMS in the presence of K2CO3 in DMF at rt to give 1-alkyl-2,2,2-trifluoro-1-trimethylsilyloxyethylphosphonate in 70-90% yields. When benzoyl phosphonates were used as starting material, after addition of CF3, the formed alcoholate undergoes phosphonate-phosphate rearrangement to form the acyl anion, followed by elimination of F- to give 1-aryldifluoroethenyl phosphates in 87-97% yields. As a representative example, vinylphosphate 6a was converted into 2,2-difluoro-1-phenylethanone 7 with 6 N HCl/EtOH/reflux or CAN/NaOH/MeOH/0 degrees C in 82-90% yields.