Synthesis and characterization of PbTe micro/nanostructures through hydrothermal method by using a novel capping agent

For the first time, a Schiff base compound derived from 1,8-diamino-3,6-dioxaoctane and 2-hydroxybenzophenone marked as (2-HBP)-(DaDo) was synthesized, characterized and then used as capping agent for the preparation of PbTe micro/nanostructures. Besides the as-synthesized Schiff base compound, Pb(NO₃)₂ and Te powders were applied as lead and telluride precursors. In addition, effect of preparation parameters like reaction time and temperature in hydrothermal synthesis on the morphology of the final products was tested. The products were analysed with the aid of SEM, XRD, FT-IR and EDS. Based on the obtained results, it was found that pure cubic phased PbTe has been obtained by this method. According to SEM images, it was found that uniform PbTe micro/nanocubes have been obtained at 180 °C for 12 h. On the other hand, by increasing the reaction temperature from 3 to 24 h, the production of cubic-like shapes increased.     

Thermodynamics of the Spin-1/2 Two-Leg Ladder Compound (C_5H_{12}N)_2CuBr_4

The thermodynamic behavior of the spin \(S=1/2\) antiferromagnetic two-leg ladder compound (C \(_5\) H \(_{12}\) N) \(_{2}\) CuBr \(_{4}\) in a uniform magnetic field is studied using numerical and analytical approaches. The entropy \(S(H,T)\) and specific heat \(C(H,T)\) are calculated. The specific heat shows various behaviors in different regions of the magnetic field. The field dependence of the specific heat is almost symmetric about the average of quantum critical fields in complete agreement with experimental results. In addition, it is found that during an adiabatic demagnetization process, temperature drops in the vicinity of the field induced zero-temperature quantum phase transitions.     

Dominant role of drivers’ attitude in prevention of road traffic crashes: A study on knowledge,attitude, and practice of drivers in Iran

Objective

Evaluating the relation between Iranian drivers’ knowledge, attitude, and practice (KAP) regarding traffic regulations, and their deterministic effect on road traffic crashes (RTCs).

Setting

Two cities of Tehran and Zahedan, Iran.

Methods

A cross-sectional study was designed. Using a simplified cluster sampling design, 2200 motor vehicle drivers including 1200 in Tehran and 1000 in Zahedan were selected. Sixty locations in Tehran and 50 in Zahedan were chosen. In each pre-identified location, 20 adult drivers were approached consecutively. A questionnaire developed by researchers was filled by each participant. The questionnaire had four sections including items assessing the demographics, knowledge, attitude and practice of drivers toward traffic regulations. Logistic regression analysis was used to evaluate the relationship between the RTCs and KAP variables.

Results

The study sample consisted of 619 (28.1%) occupational and 1580 (71.8%) private drivers. Among them, 86.4% were male. The median age was 33.6 ± 10.83. Drivers in Tehran and Zahedan had no significant differences between their mean scores of KAP items of the questionnaire. Higher knowledge, safer attitude, and safer practice were associated with a decreased number of RTC. After adjusting for possible confounders, increase of one standard deviation in attitude and practice scores (but not knowledge) resulted in 26.4% and 18.5% decrease in RTC, respectively. Finally, considering knowledge, attitude and practice of drivers in one model to assess their mutual effect, it was shown that only attitude is significantly associated with a decrease of RTC (OR = 0.76, P = 0.007).

Conclusion

Increase in attitude and practice accompanied with decreased number of RTCs in Iranian drivers. Specifically, drivers’ attitude had the crucial effect. It is not knowledge and standard traffic education; rather it is how such education is registered as an attitude that translates what is being learned into actions. Without safer attitude, even safer self-reported practice will not result in lower RTCs.     

An Efficient Palladium N‐Heterocyclic Carbene Catalyst Allowing the Suzuki–Miyaura Cross‐Coupling of Aryl Chlorides and Arylboronic Acids at Room Temperature in Aqueous Solution

The application of a highly active Pd‐NHC catalyst for the Suzuki–Miyaura cross‐coupling of a broad variety of electronically activated and deactivated aryl chlorides with different arylboronic acids in excellent yields is described. This catalyst can be handled under aerobic conditions, is active with low catalyst loadings at room temperature and in an aqueous reaction medium and allows the application of cheap potassium carbonate as the base.

     

Comparison of optimum tapered cascade and optimal square cascade for separation of xenon isotopes using enhanced TLBO algorithm

The present study is conducted to propose a new code for optimizing a multicomponent isotope separation cascade. An efficient code is developed using an enhanced TLBO algorithm with a novel mutation for calculating the optimal parameters. The results indicate that by implementing a new objective function derived from the combination of D function with total interstage flow rates, the optimum tapered cascade is more efficient than the optimal square one. Also, the best feed locations for the separation of the middle components in the square cascade are the middle stages.     

ZnS nanoparticles prepared via simple reflux and hydrothermal method: Optical and photocatalytic properties

In this research, zinc sulfide nanoparticles (NPs) with various morphologies such as spherical, flower-like, microspheres decorated with nanoparticles and nanorods were synthesized by two distinct, simple and efficient methods. These approaches include reflux and hydrothermal methods. Zinc nitrate hexahydrate (${\mathrm{Zn}({\mathrm{NO}}_3)}_2$).6H₂O were used as Zn source and thioacetamide (TAA) was used as S source. The effects of TAA to zinc ion mole ratio were investigated on the morphology, particle size, optical and photocatalytic properties of ZnS nanocrystals. In hydrothermal synthesis with increasing Zn²⁺:TAA mole ratio from 1:1 to 1:2 dendrite-like nanocrystals changed to semi-spherical nanoparticles with average particle size 50–60?nm, with different effect as photocatalysts. But any change at morphology were didn’t observed with changing Zn²⁺:TAA mole ratio from 1:1 to 1:30 in the reflux method. In the reflux method with increasing in Zn²⁺:TAA mole ratio, dispersed semi-sphere nanoparticles were observed. The synthesized nanocrystals were characterized by infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FESEM), energy-dispersive x-ray spectroscopy (EDS) and X-ray diffraction (XRD) analysis. XRD analysis and FESEM images show that the size of synthesized ZnS NPs is in the range of 15–25?nm. UV–vis spectra showed that by increasing the amount of sulfur source and increasing the reaction time, ${\lambda }_{\mathit{max}}$ shifted towards lower wavelengths, and the band gap was in the range of ~ 3.9–4.8?eV for all of the samples. Also, photoluminescence (PL) analysis showed by increasing particle size and degree of agglomeration, emission intensity (${\mathrm{\lambda }}_{\mathrm{em}}$) decreased. The photocatalytic activity of the as-prepared samples has been compared for the photocatalyst degradation of reactive blue 21. The sample with low Pl intensity has higher photocatalyst efficiency.     

A combination of CSP-based method with soft margin SVM classifier and generalized RBF kernel for imagery-based brain computer interface applications

Several methods utilizing common spatial pattern (CSP) algorithm have been presented for improving the identification of imagery movement patterns for brain computer interface applications. The present study focuses on improving a CSP-based algorithm for detecting the motor imagery movement patterns. A discriminative filter bank of CSP method using a discriminative sensitive learning vector quantization (DFBCSP-DSLVQ) system is implemented. Four algorithms are then combined to form three methods for improving the efficiency of the DFBCSP-DSLVQ method, namely the kernel linear discriminant analysis (KLDA), the kernel principal component analysis (KPCA), the soft margin support vector machine (SSVM) classifier and the generalized radial bases functions (GRBF) kernel. The GRBF is used as a kernel for the KLDA, the KPCA feature selection algorithms and the SSVM classifier. In addition, three types of classifiers, namely K-nearest neighbor (K-NN), neural network (NN) and traditional support vector machine (SVM), are employed to evaluate the efficiency of the classifiers. Results show that the best algorithm is the combination of the DFBCSP-DSLVQ method using the SSVM classifier with GRBF kernel (SSVM-GRBF), in which the best average accuracy, attained are 92.70% and 83.21%, respectively. Results of the Repeated Measures ANOVA shows the statistically significant dominance of this method at p <?0.05. The presented algorithms are then compared with the base algorithm of this study i.e. the DFBCSP-DSLVQ with the SVM-RBF classifier. It is concluded that the algorithms, which are based on the SSVM-GRBF classifier and the KLDA with the SSVM-GRBF classifiers give sufficient accuracy and reliable results.

     

Recognition and elimination of SSDF attackers in cognitive radio networks

The nature of cognitive radio (CR) technology creates a lot of opportunities for attackers. When an attack occurs, the function of the primary network is affected and thus the overall system performance will be reduced. In the present paper, we introduce and simulate a novel method for identifying spectral sensing data falsification (SSDF) attack and recognizing the malicious users (MU), which we refer to as “Recognition and Elimination of SSDF Attackers”. Our proposed scheme uses the generalized likelihood ratio test (GLRT) approach for solving the MUs detection problem. In this method, we do not need previous information about the network and number of the MUs and secondary users (SUs). In addition to detecting the occurrence of an attack, our method can recognize attackers. By recognizing the MUs, their negative effect will be eliminated and the cognitive radio network (CRN) performance will return to normal condition. Consequently, our scheme can save resources by identifying the strategy of the known attackers. Simulation results reveal that our detection and recognition scheme is better than some of methods available.

     

A Stealth Integrity Targeted Cyber‐Attack in Distributed Electric Power Networks with Local Model Information

Electric power networks are critical infrastructures, and their correct operation is of vital importance. Nowadays, these systems are prone to cyber‐attacks because of new vulnerabilities in the system and access to shared networks. In this paper, a novel Stealth Integrity Targeted Attack (SITA) is proposed in the context of distributed power systems. A distributed power system comprises several sub‐networks, or zones with dedicated control and monitoring centers. The overall system is represented by linear time invariant state space models with coupled dynamical and algebraic equations. In the proposed strategy, the attacker has access to only one of the sub networks; therefore, the attacker only requires local information about one of the power system zones. Primarily, the proposed attack policy is defined based on zero‐dynamics of the sub network. The intruder injects predesigned signals to both the local generation unit controller as well as local unsecured and controllable loads in the attacked zone. Moreover, the local measurement system, or the sensors of the targeted zone are tampered. Furthermore, it will be proved that although the neighbor zones have physical connections with the attacked zone, the injected adversary signals are designed as they do not impact other zones directly in order to conceal the local attack from neighbor control centers as much as possible. We provide some advice to system administrators to make the intrusion unfeasible or to reveal the attack. The simulations on IEEE‐118 bus test system illustrate the validity of the assertions.