Relative Distortion Research Articles

Mediating Effect of Perceived Personal Luck in the Relationship Between Narcissism and Problem Gambling in Strategic Gamblers: An Exploratory Study.

Gambling is becoming increasingly frequent among the French population, which has led to an increased number of individuals exhibiting problematic gambling patterns. Studies have found links between narcissism and cognitive distortions in relation to problem gambling, specifically among strategic gamblers, but none has tested perceived personal luck as one type of cognitive distortion in this regard. This study's purpose was to explore the relationship between narcissism, perceived personal luck and problem gambling among strategic gamblers, and to test for the mediating role of perceived personal luck in the relationship between narcissism and problem gambling. A total of 88 regular strategic gamblers were included (mean age = 37.8), with 49 non-problematic gamblers and 39 problematic gamblers. Participants completed the Problematic Gambling Severity Index, the Narcissistic Personality Inventory, and the Personal Luck Usage Scale. Results showed a significant relationship between narcissism and problem gambling, but no significant link between perceived personal luck and problem gambling and no significant mediation effect of perceived personal luck. These results may indicate a strong perception of personal skills compared to a weak perception of personal luck among problem gamblers of strategic games. This study emphasizes the importance of addressing types of gambling and types of cognitive distortions when investigating problem gambling.

Relationship between Public Expenditure and Inflation

Effective management of inflation remains one of the arduous tasks for managers of global economies. Inflation remains a macroeconomic indicator whose management outcomes have the potential to decide the electoral fortunes of elected governments and determine the purchasing power of household incomes. The purpose of this research was to assess how a steady increase in public expenditure could impact inflationary levels. The quantitative approach to scientific inquiry was adapted and used in the research. Specifically, the cross-sectional design formed the basis of the research. Data required for the research were obtained mainly from secondary sources. These included textbooks, peer-reviewed articles published in journals and grey literature. Other sources were Google Search Engine, including Netcials, MacroTrends, and databases of the World Bank and Bank of Ghana, among other significant sources. Respective data on Ghana’s annual GDP values from 1960 through 2020, annual inflation data from 1965 through 2020, changes in annual inflation rates from 1965 through 2020, and annual public expenditure values from 1983 through 2020 were collected and used in the research. Descriptive statistics and regression models were used to describe the research variables and to evaluate their behaviour over the stated time frame on inflation. The study revealed lax monetary policy as the root cause of consistently high inflationary rates over considerable periods and remained a strong contributor to the weak purchasing power of national fiat currencies. Further, relative price distortions away from their economic equilibrium are not healthy for the economy, while disinflationary policies adapted for implementation should be contingent on the causes of inflation. The single largest cost of inflation to consumers is the erosion of income, whereas higher tax rates are not the panacea for the challenges of mounting public expenditure and public debts. Respective inflation rates recorded in Ghana during 2012 (7.13%) and 1995 (59.46%) remained the lowest and highest from 1993 through 2020. Fiscal periods 2017 through 2020, 2009 through 2012, and 2005 through 2008 recorded the respective best (9.33%), second-best (11.46%) and third-best (13.32%) annual average inflation rates. With the exception of 2013 through 2016, the performance of the Ghanaian economy in relation to annual average inflationary control witnessed improvements during the second political and administrative terms compared to the first terms. However, the best annual average inflation rate over an eight-year period during the Fourth Republic was recorded from 2009 through 2016 (13.45%). Findings from the research revealed a positive and significant relationship between public expenditure and inflation (coefficient value = 1.2004653; p = 0.004, p < 0.05). Public expenditure accounted for 21.30% of the variation in inflation rate from 1983 through 2020. Results from the statistical output validated the significant influence of public expenditure on inflationary hikes, the need for monetary and fiscal policies related to inflation control to be strategically reviewed and strengthened to improve implementation outcomes, and the potential of rising public expenditure to undermine the rigidity and robustness of economic fundamentals through an unexpected surge in inflationary levels. The findings underscored the need for managers of various global economies to be keen on “economic” public expenditure to the neglect of profligate public expenditure, so the socio-economic derivatives from investments in public infrastructure would strongly add to, rather than subtract from, national development and growth efforts. The fundamental objective of MPC should be pivoted around three cardinal functions: the creation of maximum employment, moderation of long-term interest rates and ensuring price stability. Excessive public expenditure requires careful consideration by economies that whet their national development appetite with increased public infrastructure projects.

Gamma Spot Monitor at SLEGS beamline

The Gamma Spot Monitor(GSM) at SLEGS beamline is designed to provide a direct view of the gamma beam profile. The main part of the GSM is a LYSO crystal and an astronomical camera. A set of experimental tests on its performance were carried out. The results show that the magnification are 21.0% in X and 21.2% in Y direction, and the relative distortion is proved to be lower than 0.7%. The spatial resolution of the GSM evaluated by the Modulation Transfer Function(MTF) is better than 6.4 lp/mm. The contrast resolution is better than 14%. Beamline alignment is essential in beam modulation, and there are several ways for beamline alignment. In this paper, alignment capability of the GSM is demonstrated, also, the absorption coefficient distribution of a model composed of different materials is shown.

Practical Improvement of Noncontact Production Monitoring of Doping in SiC Wafers with Extended Epilayer Defects

We discuss two defect related practical improvements in the corona noncontact CV metrology, (CnCV) for SiC. The improvements are introduced in response to requests from industrial tool users. The first improvement quantifies mapping of electrically active defects with the QUAD technique (Quality, Uniformity, and Defects). It provides the capability of user selectable die grids directly comparable with Near UV-PL and optical defect mapping. This shall enhance understanding of the device killer defects and help to correlate epilayer defects and device yield. The second improvement introduces auto-remeasurement of outliers appearing in doping measurements on defective sites. This procedure is analogous to that used in the Hg probe technique and it provides a means for correcting defect related distortions in SPC doping monitoring charts.

Innovative Structural Optimization and Dynamic Performance Enhancement of High-Precision Five-Axis Machine Tools

To satisfy the requirements of five-axis processing quality, this article improves and optimizes the machine tool structure design to produce improved dynamic characteristics. This study focuses on the investigation of five-axis machine tools’ static and dynamic stiffness as well as structural integrity. We also include performance optimization and experimental verification. We use the finite element approach as a structural analysis tool to evaluate and compare the individual parts of the machine created in this study, primarily the saddle, slide table, column, spindle head, and worktable. We discuss the precision of the machine tool model and relative space distortion at each location. To meet the requirements of the actual machine, we optimize the structure of the five-axis machine tool based on the parameters and boundary conditions of each component. The machine’s weight was 15% less than in the original design model, the material it was subjected to was not strained, and the area of the structure where the force was considerably deformed was strengthened. We evaluate the AM machine’s impact resistance to compare the vibrational deformation observed in real time with the analytical findings. During modal analysis, all the order of frequencies were determined to be 97.5, 110.4, 115.6, and 129.6 Hz. The modal test yielded the following orders of frequencies: 104, 118, 125, and 133 Hz. Based on the analytical results, the top three order error percentages are +6.6%, +6.8%, +8.1%, and +2.6%. In ME’scope, the findings of the modal test were compared with the modal assurance criteria (MAC) analysis. According to the static stiffness analysis’s findings, the main shaft and screw have quite substantial major deformations, with a maximum deformation of 33.2 µm. Force flow explore provides the relative deformation amount of 26.98 µm from the rotating base (C) to the tool base, when a force of 1000 N is applied in the X-axis direction, which is more than other relative deformation amounts. We also performed cutting transient analysis, cutting spectrum analysis, steady-state thermal analysis, and analysis of different locations of the machine tool. All of these improvements may effectively increase the stiffness of the machine structure as well improve the machine’s dynamic characteristics and increases its machining accuracy. The topology optimization method checks how the saddle affects the machine’s stability and accuracy. This research will boost smart manufacturing in the machine tool sector, leading to notable advantages and technical innovations.

Design of an Airborne Low-Light Imaging System Based on Multichannel Optical Butting

For the purpose of achieving long-range, high-resolution, and ultra-wide-swath airborne earth imaging at extremely low-light levels (0.01 Lux), a low-light imaging system built on multi-detector optical butting was researched. Having decomposed the system’s specifications and verified its low-light imaging capability, we proposed to employ an optical system with a large relative aperture and low distortion and achieve imaging through the field-of-view (FOV) butting facilitated by eight 1080P high-sensitivity scientific complementary metal-oxide semiconductor (SCMOS) detectors. This paper elaborates on the design concept of the mechanical configuration of the imaging system; studies the calculation method of the structural parameters of the reflection prism; provides mathematical expressions for geometric parameters, such as the length and width of the splicing prism; and designs in detail the splicing structure of six reflection prisms for eight-channel beam splitting. Based on the design and computational results, a high-resolution, wide-swath imaging system for an ambient illuminance of 0.01 Lux was developed. Exhibiting a ground sampling distance (GSD) of 0.5 m (at a flight height of 5 km), this low-light imaging system keeps the FOV overlap ratio between adjacent detectors below 3% and boasts an effective image resolution of 4222 × 3782. The results from flight testing revealed that the proposed imaging system is capable of generating wide-swath, high-contrast resolution imagery under airborne and low-light conditions. As such, the way the system is prepared can serve as a reference point for the development of airborne low-light imaging devices.

AUTOMATED SYNTHESIS OF FAST LENSES FOR MODERN NIGHT VISION DEVICES

This article is devoted to research of the possibilities of automated design of fast and high-quality multi-lens objectives intended for use in night vision devices with modern image intensifier tubes of generation 4 and 4+, which have photocathodes with a diameter of up to 18 mm. Such image intensifier tubes are characterized by extended spectral sensitivity, high signal-to-noise ratio, and increased resolution. The computer program PODIL, developed earlier for the automated design of arbitrary optical systems, was applied to find out prescription data of fast lenses. For the parametric synthesis of optical systems, the modified evolutionary algorithm implemented in the program was used. The article presents the general methodology and results of automated parametric synthesis of a series of optical systems of objectives with different focal lengths, which contain from 7 to 9 lenses with spherical surfaces. The synthesized lenses provide angular field of view of 10°, 37° and 60° without any vignetting of axial and peripheral beams. The correspondent F numbers are 1.5, 1.33, and 1.4. The working spectral range of the designed lenses is determined by the spectral sensitivity of the photocathodes of the image intensifier tubes. In this research, it covers wavelengths from 0.45 to 0.9 μm. The longitudinal size of the designed optical systems (i.e. the distance from the first optical surface to the photocathode’s plane) is found within the range from 80 to 106 mm. The presented results of aberration analysis confirm the high image quality of the obtained optical systems. In particular, the maximum spatial frequencies of the evaluated polychromatic diffraction modulation transfer functions of the lenses over the entire field in both meridional and sagittal planes exceed 50 mm-1. The maximum values of relative distortion of the lenses are obtained within the range from 1% to 2%.

Influencing factors of industrial transformation in resource-based cities: Comprehensive measurement method based on resource price distortion

The rational allocation of industrial factors in resource-based cities is a necessary condition for promoting high-quality economic development. To systematically measure the mismatch of industrial factors, this study integrates the production function model and accounting framework of Aoki (2012). The capital, labor, and energy factors are integrated into the overall measurement framework, and the factor mismatch calculation model is innovatively constructed at the city level. To effectively reflect the factor mismatch of different cities, the relative distortion coefficient of factor price is introduced to establish the relationship between the distortion of factor-use cost and effectiveness of resource allocation. The degree and direction of factor mismatch are effectively measured. This study takes China's resource-based cities as the research object. To avoid the impact of the COVID-19 pandemic, data on 114 resource-based cities in China from 2003 to 2018 are selected, and 164 non-resource-based cities are used as the control group to evaluate the factors affecting the transformation of such cities. Regarding the diversity of resource-based cities in China, this study compares the characteristics of factor misallocation in these cities for different growth stages, geographical regions, and dominant resources. Finally, this study finds that on average, the cities' degree of energy misallocation is the most serious, and the degree of labor misallocation ranks second. The degree of capital misallocation ranks the lowest, but the misallocation of various factors is very different in different situations. Therefore, different types of cities should make detailed policy adjustments in various transformation directions according to the calculation results.

Domain Transformation of Distortion Costs for Efficient JPEG Steganography with Symmetric Embedding

Nowadays, most image steganographic schemes embed secret messages by minimizing a well-designed distortion cost function for the corresponding domain, i.e., the spatial domain for spatial image steganography or the JPEG (Joint Photographic Experts Group) domain for JPEG image steganography. In this paper, we break the boundary between these two types of schemes by establishing a theoretical link between the distortion costs in the spatial domain and those in the JPEG domain and thus propose a scheme for domain transformations of distortion costs for efficient JPEG steganography with symmetric embedding, which can directly convert the spatial distortion cost into its JPEG counterpart. Specifically, by formulating the distortion cost function for JPEG images in the decompressed spatial domain, a closed-form expression for a distortion cost cross-domain transformation is derived theoretically, which precisely characterizes the conversion from the distortion costs obtained by existing spatial steganographic schemes to those applied in JPEG steganography. Experimental results demonstrate that the proposed method outperforms other advanced JPEG steganographic schemes, e.g., JUNIWARD (JPEG steganography with Universal Wavelet Relative Distortion), JMiPOD (JPEG steganography by Minimizing the Power of the Optimal Detector), and DCDT (Distortion Cost Domain Transformation), in resisting the detection of various advanced steganalyzers.

Multiple energy price distortions and improvement of potential energy consumption structure in the energy transition

Price distortion correction is considered an effective way to improve the energy consumption structure (ECS) in the era of carbon neutrality. However, the quantitative relationship between multiple energy price distortions and ECS has not been verified from the sector's perspective. Taking China's heavy industry as the research sample, we first estimate multiple energy price distortions (including coal, oil, and natural gas) from 2003 to 2019. Then, we employ the system generalized method of moments model to explore the impact of price distortion on ECS. On this basis, we further apply the input– output price and price- shifting models to analyze potential ECS improvement resulting from price distortion correction. The main results indicate the following: (1) The price distortion of natural gas is the most serious (− 25.54%), followed by oil (−15.99%) and coal (−7.25%). (2) The effects of absolute price distortion of coal and natural gas on ECS are positive, while oil price distortion negatively affects ECS. And relative price distortion for oil negatively affects ECS, while natural gas exerts a positive effect. (3) Removing the price distortion of coal and natural gas and slightly increasing the oil price will significantly improve the ECS without price control. Eliminating distortions of coal or natural gas individually under price controls would have a greater positive impact on ECS upgrade than that under non-price control. The results may offer policy support for the low-carbon transition of China's heavy industry.

Digital loneliness-changes of social recognition through AI companions.

Inherent to the experience of loneliness is a significant change of meaningful relatedness that (usually negatively) affects a person's relationship to self and others. This paper goes beyond a purely subjective-phenomenological description of individual suffering by emphasizing loneliness as a symptomatic expression of distortions of social recognition relations. Where there is loneliness, a recognition relation has changed. Most societies face an increase in loneliness among all groups of their population, and this sheds light on the reproduction conditions of social integration and inclusion. These functions are essential lifeworldly components of social cohesion and wellbeing. This study asks whether "social" AI promotes these societal success goals of social integration of lonely people. The increasing tendency to regard AI Companions (AICs) as reproducers of adequate recognition is critically discussed with this review. My skepticism requires further justification, especially as a large portion of sociopolitical prevention efforts aim to fight an increase of loneliness primarily with digital strategies. I will argue that AICs rather reproduce than sustainably reduce the pathodynamics of loneliness: loneliness gets simply "digitized."

Manifestation of chemical pressure: Magnetism and magnetostriction in nanoscale RFeO3 (R = Sm, Dy, Ho, and Lu)

AbstractThe effect of ionic radii sizes on magnetostriction is studied in relation to structural and magnetic properties. To explore the effect of the chemical pressure, nanoparticles of rare‐earth (RE) orthoferrites, SmFeO3, DyFeO3, HoFeO3, and LuFeO3 are studied using X‐ray diffraction, field emission scanning electron microscopy, and Raman spectroscopy. Magnetic and magnetostriction measurements are also performed. In these orthoferrites, the coordination of the RE ion is eightfold, whereas the RE ionic radii are significantly different, which directly influences the structural parameters. The distortion of FeO6 octahedra is observed as a result of changing chemical pressure within the lattice. The different magnitudes of magnetostriction in RE orthoferrites can be attributed to the different degrees of distortion of FeO6 octahedra, R–O dynamics, and spin–orbit interactions in the system. The maximum value of magnetostriction (∼ 19 ppm) and magnetization at 2 K (30.64 emu/g) is demonstrated by HoFeO3. Comparison of structural parameters of the samples to their respective bulk counterparts indicated relative structural distortion in nanoparticles.

Differences between the true reproduction number and the apparent reproduction number of an epidemic time series

The time-varying reproduction number R(t) measures the number of new infections per infectious individual and is closely correlated with the time series of infection incidence by definition. The timings of actual infections are rarely known, and analysis of epidemics usually relies on time series data for other outcomes such as symptom onset. A common implicit assumption, when estimating R(t) from an epidemic time series, is that R(t) has the same relationship with these downstream outcomes as it does with the time series of incidence. However, this assumption is unlikely to be valid given that most epidemic time series are not perfect proxies of incidence. Rather they represent convolutions of incidence with uncertain delay distributions. Here we define the apparent time-varying reproduction number, RA(t), the reproduction number calculated from a downstream epidemic time series and demonstrate how differences between RA(t) and R(t) depend on the convolution function. The mean of the convolution function sets a time offset between the two signals, whilst the variance of the convolution function introduces a relative distortion between them. We present the convolution functions of epidemic time series that were available during the SARS-CoV-2 pandemic. Infection prevalence, measured by random sampling studies, presents fewer biases than other epidemic time series. Here we show that additionally the mean and variance of its convolution function were similar to that obtained from traditional surveillance based on mass-testing and could be reduced using more frequent testing, or by using stricter thresholds for positivity. Infection prevalence studies continue to be a versatile tool for tracking the temporal trends of R(t), and with additional refinements to their study protocol, will be of even greater utility during any future epidemics or pandemics.

Comparative Deep Learning Models in Applications of Steganography Detection

This paper explores the use of deep learning algorithms in steganography detection. More specifically, it examines deep learning-based binary classification to distinguish between stego and non-stego images from the three steganography algorithms, The Wavelet Obtained Weights (WOW), Spatial Universal Wavelet Relative Distortion (S-UNIWARD), Highly Undetectable Steganography (HUGO). It also highlights the lack of research to develop a practical universal image steganography detection system using trained deep learning. The proposed farmwork combines multiple detection deep learning architectures to create a universal Deep Convolutional Neural Network (Deep-CNN). In this paper, we evaluate Deep-CNN-based image steganography detection techniques trained on images extracted from the three steganography algorithms. The dataset consists of 10,000 images in PGM format, which is converted to JPG format with a size of 256256 pixels. The data set is classified into clear and stego images, which are the same image samples used in each category, with the three separate data sets for stego images created using three algorithms (WOW, S-UNIWARD, and HUGO). The results show a slight decrease in detection accuracy, but the fine-tuning of the improved deep-CNN architecture performs better than other methods.

AUTOMATED DESIGN OF KORSCH ORTHOSCOPIC ASPHERICAL MIRROR TELESCOPES FOR NANOSATELLITES

This study presents the results of an automated parametric synthesis of a series of orthoscopic aspheric optical systems of mirror telescopes with different focal lengths, built according to the Korsch scheme. In order to ensure compactness of the design, these systems consist of three second-order aspheric mirrors and three folded flat mirrors. The obtained optical systems have a focal length ranging from 480 mm to 960 mm, an angular field of view ranging from 1.2° to 2.4°, an aperture number ranging from 6 to 12, an entrance aperture with a diameter of 80 mm, and an axial length of no more than 170 mm, which is within the dimensions of a 2U CubeSat. The maximum linear size of the image detector's sensitive area is 20 mm in all considered systems. The mirror telescopes do not have chromatic aberrations, enabling the capture of images within the visible spectrum and multiple infrared sub-bands. The provided aberration analysis demonstrates the high image quality of the considered optical systems. Specifically, for a wavelength of 0.546 μm, thediffraction modulation transfer function values both in the meridional and sagittal planes across the entire field exceed 0.53 for a spatial frequency of 30 mm-1, and 0.3 for a spatial frequency of 50 mm-1. The maximum relative distortion in the designed systems is 0.005%, corresponding to an absolute displacement of 0.5 μm. The presented telescopes are capable of covering an observation band of Earth's surface with linear dimensions ranging from 12.6 km to 25.1 km when a satellite track height is 600 km. By applying multi-element image detectors with a pixel size of 5 μm and achieving diffraction-limited image quality in the optical systems, both the geometric and diffraction resolution limits on Earth's surface will not exceed 10 m.

Theoretical Analysis of a Three-Component Reaction between Two Diazo Compounds and a Hydroxylamine Derivative: Mechanism, Enantioselectivity, and Effect of Cooperative Catalysis.

The mechanism, enantioselectivity, and effect of chiral phosphoric acid (CPA) cocatalyst were investigated by the density functional theory (DFT) for the three-component asymmetric aminohydroxylation between two diazo compounds and a hydroxylamine derivative. This type of cascade process is cooperatively catalyzed by Rh2(OAc)4 and CPA. The obtained results clearly indicate that the first step of the global reaction involves a nucleophilic attack at the nitrogen center of N-hydroxyaniline by rhodium-carbene intermediates producing imines. Subsequently, an enolate intermediate was recognized as the key species generated from the second diazo compound and the leaving benzyl alcohol (BnOH) fragment of the first step and in the presence of the same dirhodium catalyst. Then, the reaction is terminated by the asymmetric Mannich-type addition, delivering the aminohydroxylation products of an S-R conformation with the assistance of chiral phosphoric acid. The distortion/interaction analysis shows that the relative distortions of CPA and the enol play a vital role in the energy ordering of the stereocontrolling transition states (TSs). Furthermore, the influence of different substituents in CPA was fully rationalized by distortion/interaction analysis. This study opens up novel synthetic possibilities and improves the reaction predictability when exploring the related types of cooperatively catalyzed organic transformations.

Exploring the short and long-range order in connection with fluorine content in mixed anions copper hydroxyfluorides

Hydroxyl-rich (Cu-LF) and Fluorine-rich (Cu–HF) copper hydroxyfluorides Cu(OH)2-xFx (x = 0.4–0.5 and x = 0.9–1.5) were prepared by precipitation route followed by hydrothermal process where the starting pH and the HF molar content play a key role. Based on powder XRD and PDF analysis, long range and short order were evidenced with various Cu–O/F bondlengths illustrating the Jahn-teller distortion as well as the Cu–Cu intra-sheet and interslab interactions. Tuning the fluorine content allows chemical bonding modulation by antagonist effect, resulting for instance in the weakening of H bonding in the hydroxyl-rich compound. When the fluorine content increases, the average structures evolve from a disordered network with a random distribution of anions in the vicinity of Cu2+ in Cu-LF to a well ordered mixed anions phase where Cu(OH)3F3/Cu(OH)2F4/Cu(OH)5F distorted octahedra are close to C2h point group symmetry. Raman spectroscopy confirm the average structural features with the point group symmetry. One should outline in Cu–HF composition, stronger CuF3(OH)3 octahedron stiffness associated to a stretching O–H mode at lower frequency, synonymous of O–H bond weakening and consequently stronger hydrogen bonding in agreement with PDF analysis. UV–visible–NIR spectra show in Cu–HF hydroxyfluoride, an increase of the optical band gap of 0.6 eV and a decrease of Cu2+(3 d9) crystal field splitting of 0.1 eV in agreement with the larger fluorine content. However, the dxz-dyz orbital splitting increases of 0.2 eV in Cu–HF in good agreement with the C2h point group symmetry and the related distortion. Finally, whereas the hydroxyl-rich Cu-LF phase decomposes into CuO at T > 300 °C, the Fluorine rich Cu–HF compound lead at T > 320 °C to the formation of CuF2, Cu2O in addition to CuO. This unusual reduction process Cu2+ → Cu+ at low temperature is associated to the strengthening of Cu–O/F and Cu–Cu bonding in the basal plane of Cu(OH)3F3 distorted octahedron.

Hypericum perforatum L. protects against renal function decline in ovariectomy rat model by regulating expressions of NOS3 and AKT1 in AGE-RAGE pathway

BackgroundHypericum perforatum L. (HPL) is a potential traditional Chinese medicine. It could promotes menopausal 'kidney-yin deficiency syndrome' that characterized by renal function decline. However, its potential pharmacological effect and mechanism remains unknown. ObjectiveThe aim of this study was to investigate whether HPL can improve menopausal renal function decline and to explore its mechanism of action. MethodsThe mainly ingredients of HPL were identified using UPLC-Q-TOF-MS/MS approach, and the potential therapeutic targets of HPL for renal function decline were chose via network pharmacology technique. The key therapeutic metabolites were selected through non-targeted metabolomic and chemometric methods. Then, the network were constructed and the key targets and metabolites were screened. At last, the validation experiments and mechanism exploring were adopted by using Immunofluorescence, enzyme-linked immunosorbent assay (ELISA), real-time PCR (RT-PCR), and western blotting assays. Resultsmainly ingredients of HPL were identified and determined 17 compounds and 29 targets were chose as mainly active compounds and potential therapeutic targets. Based on OVX induced renal decline rat model, after chemometric analysis, 59 endo-metabolites were selected as key therapeutic metabolites, and AGE-RAGE signal pathway in diabetes complications was enriched as the key pathway. By constructing a "disease-component-target" network, Hyperoside, Quercetrin, and quinic were selected as the key therapeutic compounds, and the AKT1 and NOS3 were selected as the key therapeutic targets. The results of ELISA, RT-PCR and western blot experiments indicated that HPL could rescue the abnormal expressions both of AKT1 and NOS3, as well as their related metabolites distortion. ConclusionOur findings indicated that HPL regulated expression of AKT1 and NOS3 through modulating AGE-RAGE signaling pathway in OVX stimulated rats` renal dysfunction, implicating the potential values of HPL in menopause syndromes therapy.

Electronic structure, and dielectric, magnetic and reflection-loss behaviors of BaFe12-xMnxO19 (0 < x ≤ 2) hexaferrites

M−type hexaferrites doped with transition metals are important materials used widely in modern electronic devices. Although many research works considered their magnetic properties, the relation between their electronic structure and electromagnetic behaviors have been less taken into account, particularly Mn-doped M−type hexaferrites. This work presents a detailed study on the electronic structure, and dielectric, magnetic and reflection-loss behaviors of BaFe12-xMnxO19 (x = 0.5, 1 and 2) hexaferrite specimens prepared by conventional solid-state reactions. The analysis of X-ray absorption spectra proves a mixed oxidation state of Fe2+,3+ and Mn2+,3+ ions, and chemical shifts of Fe2+ → Fe3+ and Mn2+ → Mn3+ when x increases from 0.5 to 2. These factors change the unit-cell volume, and cause Mn3+-related Jahn-Teller distortions. Concurrently, the saturation magnetization Ms varies in the range from 24 to ∼31 emu/g, which is associated with interaction competitions between Fe2+,3+-Mn2+,3+ pairs and Fe2+-related spin canting. Having studied electromagnetic behaviors, we have found strong changes in values of the permittivity and permeability at frequencies f = 10∼15 GHz. For a thickness t = 2.4 mm, reflection-loss magnitudes of microwave are about 10 ∼ 11 dB (corresponding to above 90% microwave being absorbed), with an absorption bandwidth of ∼3 GHz. Assessments of the magnetic and dielectric loss tangents, and Cole-Cole curves indicate electrical energy dissipation associated with interfacial/dipolar polarizations and conductive loss playing a dominant role in microwave absorption of BaFe12-xMnxO19.

Extraction Method of Secret Message Based on Optimal Hypothesis Test

As the ultimate goal of steganalysis, secret message extraction plays a decisive role in obtaining secret communication evidence and cracking down on criminal activities. For STC (Syndrome-Trellis Codes)-based adaptive steganography, existing pioneering work on secret message extraction: the method based on run test under plaintext embedding may misjudge incorrect stego key as correct stego key, resulting in the failure of extraction. To avoid such a situation, this manuscript proposed a secret message extraction method based on optimal hypothesis test with 100% accuracy under plaintext embedding. First, it is proved that there is a probability distribution difference between the sub-sequence extracted by correct and incorrect stego key. Then, based on the difference, an optimal hypothesis test model is designed to recover the correct stego key. Finally, given the probability of type I and II errors, the sample size and threshold in the hypothesis test are derived. Classic adaptive steganography such as HUGO (Highly Undetectable Steganography) and J-UNIWARD (JPEG Universal Wavelet Relative Distortion) have been conducted experiment, showing that the proposed method can extract message with 100% accuracy and 44 bits sample size, which verifies the correctness of the theorem and the effectiveness of the method.