A Spectroscopic Study of Charge Distribution in Transition Metal Bridging Hydride Complexes

A series of transition metal bridging hydrides of general formula C[μ-HM2(CO)10] (C = tetraethylammonium, Et4N+; tetraphenylphosphonium, Ph4P+; of bis(triphenylphosphine)iminium, PPN+; M = Cr or W) were synthesized from M(CO)6 and NaBH4 bt known methods. As a means of obtaining information about the charge distribution in these complexes, they were allowed to interact in solution and the solid state with triphenylphosphine oxide (TPPO) on the premise that this electron donor could identify sites of relative electron deficiency. Evidence for interaction was sought via solution and solid state infrared (IR) spectroscopy and solution 1H nuclear magnetic resonance (NMR) spectroscopy. Solution IR spectra for mixtures of TPPO and complexes in a number of ratios were examined for changes in the bands associated with CO stretching, PO stretching, and MCO bending motions. For comparison, spectra of mixtures of TPPO with Ph4PCl and Et4NBr were also collected. Spectral alterations suggest that TPPO associates with both the cation and anion in [Ph4P][μ-HM2(CO)10] (M = Cr, W). Evidence is presented that more than one site on the anion in these complexes is involved and that one of these is the carbon atom of an equatorial CO ligand. This result supports proposed mechanisms for reactions of transition metal carbonylates that are catalyzed by TPPO. In contrast, spectra for mixtures with [Et4N]-[μ-HW2(CO)10] suggest that there is little or no association with TPPO in these samples. This is interpreted as arising because interactions with TPPO are inhibited by substantial ion pairing for this cation-anion combination. All of the spectra show conclusively that TPPO does not associate with a metal atom in any of the mixtures studied. The solution IR spectra provided no direct information regarding interaction of TPPO with the bridging hydrogen atom. The solid state IR spectra of mixtures of the complexes and TPPO inseveral ratios show no evidence for adduct formation. In 1H NMR spectra of the mixtures, the chemical shifts of the bridging hydrogen atoms are altered only slightly from their values in the pure complexes. In view of the presumed low sensitivity of this parameter to weak interactions involving a bridging hydrogen, this result is regarded as neither strongly supporting nor ruling out an association of TPPO with the bridging atom

Pre-IdentifyNet: An Improved Neural Network for Image Recognition

With the rise and development of artificial intelligence, image recognition and classification technology has received more and more attention as an important branch of its research field. Among them, the introduction of deep learning networks and the construction of neural network structures not only avoid a lot of the tedious work of manual extraction, but also improve the accuracy of image recognition. Convolutional neural networks have many advantages that conventional neural networks do not have. Therefore, image classification systems based on convolutional neural networks emerge in endlessly, but there is still much room for improvement in terms of recognition accuracy and recognition speed. Based on this, this paper proposes an improved deep convolutional neural network to improve the accuracy of the network by changing a series of parameters such as the number of channels of the convolution layer, the size of the convolution kernel, the learning rate, the number of iterations, and the size of the small batch with speed. In this paper, three data sets were selected, namely sewage, animals and the Simpson Family. Comparing the improved convolutional neural network network with the existing SqueezeNet and GoogleNet. It is found that the accuracy of the network is maintained while maintaining a similar speed. Both F1-score and F1-score have been improved with a higher recognition rate and better recognition effect in image recognition classification

Sustainable development efficiency and its influencing factors across BRICS and G7 countries: An empirical comparison

Sustainable development is the global overarching paradigm and essential for achieving economic, social, and environmental development. The primary goal of this study is to compare the efficiency of sustainable development and evaluate its influencing factors across the BRICS (Brazil, Russia, India, China, and South Africa) and G7 (Canada, France, Germany, Italy, Japan, the United Kingdom, and United States) countries by examining total factor productivity, efficiency change, and technological change. For this, we adopted the super-efficiency SBM-DEA model with undesirable output and Global Malmquist-Luenberger (GML) productivity index model to overcome inaccurate efficiency results while avoiding environmentally unwanted outputs and to resolve the shortcomings of the conventional Malmquist-Luenberger index. It is also necessary to explore relevant influencing factors on the environmental pollution thereby affects the sustainable development efficiency of the study countries, thus, this study employed STIRPAT approach. A panel data of BRICS and G7 countries from 2005 to 2015 is used. The findings reveal that sustainable total factor productivity (GML) in China (1.0165), the US (1.0150), and UK (1.0024) is on the rise. China is also one of the countries that experienced the highest positive efficiency change (GMLEC) (1.0147) and the US has the highest positive technical change (GMLTC) (1.0103). Contrarily, Russia experienced the highest decline in GMLTC (0.9316) as well as GML indexes (0.9337), whereas South Africa experienced the highest decline in GMLEC (0.9707). Additionally, GDP per capita (.0969) and population (.4178) have a positive influence on CO2 emissions in the BRICS countries, whereas in the G7 nations, GDP per capita (−.2180) and population (−.1249) have negative influences on CO2 emissions. The study also offers practical recommendations to address identified limitations and improve sustainable productivity and environmental efficiency. The inverse link between GDP and CO2 emissions might imply that the G7 nations have passed the turning point on an environmental Kuznets curve (EKC), but this finding does not support the EKC hypothesis in the BRICS nations

Muscle activity-driven green-oriented random number generation mechanism to secure WBSN wearable device communications

Wireless body sensor networks (WBSNs) mostly consist of low-cost sensor nodes and implanted devices which generally have extremely limited capability of computations and energy capabilities. Hence, traditional security protocols and privacy enhancing technologies are not applicable to the WBSNs since their computations and cryptographic primitives are normally exceedingly complicated. Nowadays, mobile wearable and wireless muscle-computer interfaces have been integrated with the WBSN sensors for various applications such as rehabilitation, sports, entertainment, and healthcare. In this paper, we propose MGRNG, a novel muscle activity-driven green-oriented random number generation mechanism which uses the human muscle activity as green energy resource to generate random numbers (RNs). The RNs can be used to enhance the privacy of wearable device communications and secure WBSNs for rehabilitation purposes. The method was tested on 10 healthy subjects as well as 5 amputee subjects with 105 segments of simultaneously recorded surface electromyography signals from their forearm muscles. The proposed MGRNG requires only one second to generate a 128-bit RN, which is much more efficient when compared to the electrocardiography-based RN generation algorithms. Experimental results show that the RNs generated from human muscle activity signals can pass the entropy test and the NIST random test and thus can be used to secure the WBSN nodes

Fluorescent Properties of ZnO Nanostructures Fabricated by Hydrothermal Method

ZnO nanorods with mean diameter 200 nm on different substrates were fabricated by hydrothermal method. Fluorescent properties of fabricated ZnO nanorods were researched by both linear and nonlinear excitation using femtosecond lasers. The damage threshold of productions on Si substrate irradiated under intense femtosecond pulses was found much higher than that on Zn plate. Raman spectrum was also applied to investigate relative optical properties. The A1L optical mode was found to be important to the fluorescent properties of ZnO materials

Finding Small Solutions of the Equation Bx−Ay=zBx-Ay=z and Its Applications to Cryptanalysis of the RSA Cryptosystem

In this paper, we study the condition of finding small solutions $(x,y,z)=(x_0, y_0, z_0)$ of the equation $Bx-Ay=z$. The framework is derived from Wiener\u27s small private exponent attack on RSA and May-Ritzenhofen\u27s investigation about the implicit factorization problem, both of which can be generalized to solve the above equation. We show that these two methods, together with Coppersmith\u27s method, are equivalent for solving $Bx-Ay=z$ in the general case. Then based on Coppersmith\u27s method, we present two improvements for solving $Bx-Ay=z$ in some special cases. The first improvement pays attention to the case where either $\gcd(x_0,z_0,A)$ or $\gcd(y_0,z_0,B)$ is large enough. As the applications of this improvement, we propose some new cryptanalysis of RSA, such as new results about the generalized implicit factorization problem, attacks with known bits of the prime factor, and so on. The motivation of these applications comes from oracle based complexity of factorization problems. The second improvement assumes that the value of $C \equiv z_0\ (\mathrm{mod}\ x_0)$ is known. We present two attacks on RSA as its applications. One focuses on the case with known bits of the private exponent together with the prime factor, and the other considers the case with a small difference of the two prime factors. Our new attacks on RSA improve the previous corresponding results respectively, and the correctness of the approach is verified by experiments

Towards Evaluating Pitch-Related Phonation Function in Speech Communication Using High-Density Surface Electromyography

Pitch, as a sensation of the sound frequency, is a crucial attribute toward constructing a natural voice for communication. Producing intelligible sounds with normal pitches depend on substantive interdependencies among facial and neck muscles. Clarifying the interrelations between the pitches and the corresponding muscular activities would be helpful for evaluating the pitch-related phonating functions, which would play a significant role both in training pronunciation and in assessing dysphonia. In this study, the speech signals and the high-density surface electromyography (HD sEMG) signals were synchronously acquired when phonating [a:], [i:], and [ә:] vowels with increasing pitches, respectively. The HD sEMG energy maps were constructed based on the root mean square values to visualize spatiotemporal characteristics of facial and neck muscle activities. Normalized median frequency (nMF) and root-mean square (nRMS) were correspondingly extracted from the speech and sEMG recordings to quantitatively investigate the correlations between sound frequencies and myoelectric characteristics. The results showed that the frame-wise energy maps built from sEMG recordings presented that the muscle contraction strength increased monotonously across pitch-rising, with left-right symmetrical distribution for the face/neck. Furthermore, the nRMS increased at a similar rate to the nMF when there were rising pitches, and the two parameters had a significant correlation across different vowel tasks [(a:) (0.88 ± 0.04), (i:) (0.89 ± 0.04), and (ә:) (0.87 ± 0.05)]. These findings suggested the possibility of utilizing muscle contraction patterns as a reference for evaluating pitch-related phonation functions. The proposed method could open a new window for developing a clinical approach for assessing the muscular functions of dysphonia