A comparison of the effect of alendronate and You-Gui-Wan on osteoporosis in female rats with kidney-yang deficiency

Background:In traditional Chinese medicine,You-Gui-Wan(YGW)is typically used to treat osteoporosis associated with kidney-yang deficiency.However,there have been few mechanistic studies on the effectiveness of kidney-yang deficiency-type osteoporosis with YGW.To further clarify the role of YGW in the effect of osteoporosis with kidney-yang deficiency,the study analyzed the therapeutic advantages of YGW by comparing the therapeutic effects of YGW and alendronate(ALN)on osteoporosis with kidney-yang deficiency.Methods:SPF female SD rats were randomly divided into control,osteoporosis,osteoporosis with kidney-yang deficiency,osteoporosis with kidney-yang deficiency+YGW and osteoporosis with kidney-yang deficiency+ALN groups.Except for the control group,osteoporosis was induced by the removal of bilateral ovaries.After 12 weeks,rats with osteoporosis in the kidney-yang deficiency group had kidney-yang deficiency syndrome triggered by hydrocortisone for 14 days.Rats were treated with YGW or ALN for 12 weeks.The weights of rats were recorded.Hematoxylin-eosin staining staining was used to observe pathological changes in bone trabeculae,liver,spleen,and kidneys of rats.Depletion of the growth plate cartilage of rats in different groups was observed by safranine-O staining.The expression of osteoclast key indices(ACP)and osteoblast key indices(ALP)in the bone tissue of rats in the different groups was observed by immunohistochemical staining.The expression of bone resorption-related indicators(TRAP and NXT-1),bone formation-related indicators(BALP,BGP,and P1NP),and major indicators of kidney-yang deficiency(ACTH,T3,T4,cAMP,and cGMP)were observed using an ELISA detection kit.The expression levels of the main indices of liver function(ALT and AST)were detected in different groups.Results:The differences between the osteoporosis with kidney-yang deficiency group and osteoporosis group were that the weight of rats and the expression of ACTH,T3,T4,and cAMP decreased significantly,and the expression of cGMP increased in the osteoporosis with kidney-yang deficiency group.Moreover,both YGW and ALN effectively improved the symptoms of osteoporosis,including the injury of bone trabeculae and growth plates,as well as the expression of bone metabolism-related indicators.However,unlike ALN,YGW simultaneously ameliorated the expression of key indicators of kidney-yang deficiency and prevented weight loss in rats.In addition,YGW caused no obvious damage to the liver,spleen,or kidney,whereas ALN led to liver cirrhosis.Conclusion:The results reveal that YGW plays a crucial part in osteoporosis with kidney-yang deficiency,increases bone mineral density,and improves bone metabolism indicators,and is safe and efficient for the efficacy of osteoporosis with kidney-yang deficiency.YGW might have a better therapeutic effect on osteoporosis in patients with kidney-yang deficiency.Therefore,alendronate should be used cautiously in patients with osteoporosis and poor liver function.

Properties of Flare Events on M Stars from LAMOST Spectral Survey Based on Kepler and TESS Light Curves

A catalog of M stars has been published from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope data release 7(LAMOST DR7).We cross-matched the LAMOST M catalog with Kepler,Kepler 2(K2)and Transiting Exoplanet Survey Satellite(TESS)surveys.We obtained the light curves from the Kepler and TESS surveys.We detected 20,047 flare events from 4053 M stars and calculated their durations,amplitudes,and energies.We analyzed the distribution of the flare durations and energies.The distributions of flare duration for Kepler,K2 and TESS peak are at 3–3.5 hr,4–6 hr and 1–1.5 hr,respectively.This may be the result of the different cadences for the three data sets.The highest regions of the flare energies of Kepler,K2 and TESS are 32–32.5,32–32.5 and31–31.5 erg in Log format,respectively.A linear relationship between flare duration and energy emerges from our analysis.The ratio of flare duration to total observational time is approximately 0.2%–0.3%for the Kepler,K2 and TESS surveys.The occurrence rate of a star with a flare event increases from the M0 to M4 subtypes.We also determined the spatial distribution of the flare rate of M stars in the Milky Way.It seems that the flare rate decreases as the vertical height increases.The power index of the flare energies is in the region of 1.53–2.32,which is similar to previous result for solar type star(2.0).Further,we examined the relationship between the flare amplitude and chromospheric intensity.The flare activity increases rapidly with the increase in the HαEW at the lower values(less approximately 2?)and it increases slowly at the higher values.

Network Garment Style Design System with Remote Information Access and Auto-Connecting Technology

A Network Garment Style Design System (NGSDS) is proposed to enable the remote style structure drawing design of garment. After the development of the system structure based on network that consists of client end and server end at two remote places, a multi-layer part database based on Oracle platform is presented to store information of different parts of garment style. With the acquirement of remote design data at server end using Http technology, the style design is ultimately implemented at the client end using Auto-connecting algorithms. One empirical example is given to show the implementation of the NGSDS.

Effect of cold stratification on the temperature range for germination of Pinus koraiensis

Germination at low spring temperatures may offer a competitive advantage for the growth and survival of plant species inhabiting temperate forest ecosystems.Pinus koraiensis is a dominant species in temperate forests of northeastern China.Its seeds exhibit primary morphophysiological dormancy following dispersal in autumn,limiting natural or artificial regeneration:direct seeding and planting seedlings in spring.The aim of this study was to determine the optimum cold stratification temperature that induces germination to increase towards lower temperatures.Seeds from two populations(Changbaishan and Liangshui)were cold stratified at 0,5 and 10℃.Germination to incubation temperatures(10/5,20/10,25/15 and 30/20℃;14/10 h day/night)were determined after 2 and 4 weeks,and 5.5 and6.5 months of cold stratification.After 5.5 months,approximately 68-91%of seeds from both populations germinated at incubation temperatures of 25/15℃and 30/20℃,regardless of cold stratification temperatures.When the cold stratification temperature was reduced to 0℃and the period increased to 6.5 months,germination at 10/5℃significantly improved,reaching 37%and 64%for the Changbaishan and Liangshui populations,respectively.After 6.5 months of cold stratification,there was a significant linear regression between cold stratification temperatures and germination at10/5℃.The range in temperatures allowing for germination gradually expanded to include lower temperatures with decreasing cold stratification temperatures from 10 to 5℃and further to 0℃.

Modeling of Sensor Enabled IrrigationManagement for Intelligent Agriculture Using Hybrid Deep Belief Network

Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual agriculture.Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture.Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques.Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist.With this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent agriculture.The MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination purposes.Besides,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not needed.The MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.

An anonymous authentication and secure data transmission scheme for the Internet of Things based on blockchain

With the widespread use of network infrastructures such as 5G and low-power wide-area networks,a large number of the Internet of Things(IoT)device nodes are connected to the network,generating massive amounts of data.Therefore,it is a great challenge to achieve anonymous authentication of IoT nodes and secure data transmission.At present,blockchain technology is widely used in authentication and s data storage due to its decentralization and immutability.Recently,Fan et al.proposed a secure and efficient blockchain-based IoT authentication and data sharing scheme.We studied it as one of the state-of-the-art protocols and found that this scheme does not consider the resistance to ephemeral secret compromise attacks and the anonymity of IoT nodes.To overcome these security flaws,this paper proposes an enhanced authentication and data transmission scheme,which is verified by formal security proofs and informal security analysis.Furthermore,Scyther is applied to prove the security of the proposed scheme.Moreover,it is demonstrated that the proposed scheme achieves better performance in terms of communication and computational cost compared to other related schemes.

Chinese New Year Folk Culture Adds Impetus to Guizhou's Colorful Tourism Economy

During the Chinese New Year in 2024,a series of traditional folk activities were held all over Guizhou,attracting a large number of travelers,with the number of received travelers and comprehensive income of Guizhou reaching a new high.

Cold Damage Risk Assessment of Double Cropping Rice in Hunan, China

Combined with remote sensing data and meteorological data, cold damage risk was assessed for planting area of double cropping rice （DCR） in Hunan Province, China. A new methodology of cold damage risk assessment was built that apply to grid and have clear hazard-affected body. Each station cold damage annual frequency and average annual intensity of cold damage was calculated by using 1951-2010 station daily mean temperature and simple cold damage identification index. On this basis, average annual cold damage risk index was obtained by their product. The spatial analysis models of cold damage risk index about double-season early rice （DSER） and double-season later rice （DSLR） were established respectively by the relation of average annual cold damage risk index and its geographic factors. Critical threshold of level of average annual cold damage risk index for DSER and DSLR were respectively divided by the correlative equation of cold damage annual frequency and average annual intensity of cold damage. 2001-2010 planting area of DCR, acquired by time series analysis of MOD09AI 8-d composite land surface reflectance product, was as target of assessment. The results show average annual intensity of cold damage is exponential function of cold damage annual frequency, average annual cold damage risk index is directly proportional to cold damage cumulant and cold damage annual frequency, and is inversely proportional to happen times of cold damage and the square of statistical time sequence length. Cold damage risk of DSER is higher than DSLR in Hunan Province. In the 10-yr stacking map, DCR planting in low risk area accounted for 11.92% of total extraction area, in moderate risk area accounted for 69.62%, in high risk area accounted for 18.46%. According to the cold damage risk assessment result, DCR production can be guided to reduce cold damage losses.

A VLIW Architecture Stream Cryptographic Processor for Information Security

As an important branch of information security algorithms,the efficient and flexible implementation of stream ciphers is vital.Existing implementation methods,such as FPGA,GPP and ASIC,provide a good support,but they could not achieve a better tradeoff between high speed processing and high flexibility.ASIC has fast processing speed,but its flexibility is poor,GPP has high flexibility,but the processing speed is slow,FPGA has high flexibility and processing speed,but the resource utilization is very low.This paper studies a stream cryptographic processor which can efficiently and flexibly implement a variety of stream cipher algorithms.By analyzing the structure model,processing characteristics and storage characteristics of stream ciphers,a reconfigurable stream cryptographic processor with special instructions based on VLIW is presented,which has separate/cluster storage structure and is oriented to stream cipher operations.The proposed instruction structure can effectively support stream cipher processing with multiple data bit widths,parallelism among stream cipher processing with different data bit widths,and parallelism among branch control and stream cipher processing with high instruction level parallelism;the designed separate/clustered special bit registers and general register heaps,key register heaps can satisfy cryptographic requirements.So the proposed processor not only flexibly accomplishes the combination of multiple basic stream cipher operations to finish stream cipher algorithms.It has been implemented with 0.18μm CMOS technology,the test results show that the frequency can reach 200 MHz,and power consumption is 310 mw.Ten kinds of stream ciphers were realized in the processor.The key stream generation throughput of Grain-80,W7,MICKEY,ACHTERBAHN and Shrink algorithm is 100 Mbps,66.67 Mbps,66.67 Mbps,50 Mbps and 800 Mbps,respectively.The test result shows that the processor presented can achieve good tradeoff between high performance and flexibility of stream ciphers.

Security Defence Policy Selection Method Using the Incomplete Information Game Model

Nowadays, the network defence policy selection using game model of incomplete information ignores the type of the defender, which quantifies cost simply, resulting in unreasonable defence policies selection. Aiming at the problem, we use Bayesian game theory to model the active defence policy selection. We take the types of both the attacker and the defender into consideration. Besides, the traditional quantization method is enhanced. Then, we calculate the equilibrium of static Bayesian game. Based on the analysis of the equilibrium, we select the optimal defence policy through the prediction for attackers' actions. The paper calculates the defence effectiveness of defence policies and provides a defence policies selection algorithm. Ultimately, we present an example to verify the effectiveness of the method and model proposed in the paper.

Luminescence of Co-doped SrTiO_3:Pr^(3+)

The SrTiO3 ： Pr^3＋ material, co-doped with monovalent Li^＋ , divalent Mg^2＋ , and trivalent Al^3＋ was prepared by a new sol-gel method. The phase and crystallinity of the synthesized materials were investigated by powder X-ray diffraction（XRD） and scanning electron microcopy（SEM）. Among the co-doped ion, Al^3＋ incorporation caused the least lattice change and had the best crystallinity. Photoluminescence spectra were taken to investigate the luminescence characteristics. We observed a red luminescence change of SrTiO3 ： Pr^3＋ after being co-doped, and a best enhancement on the red luminescence with the trivalent Al^3＋ was observed. The present results indicated that the charge defect associated with Al^3＋ has led to charge compensation of Pr^＋ and also implied that the charge defects（usually the second dopant ions replacing the A or B sites in the lattice） which are closer to PrSr^＋ contribute more to the red luminescence enhancement.

Negative Imaginary Approached High Performance Robust Resonant Controller Design for Single-Phase Islanded Microgrid and Its Voltage Observation on Different Load Condition

This paper presents the design of a high performance robust resonant controller for the islanded single-phase microgrid operation on different loads conditions. The design of the controller is done using the results of Negative Imaginary approach. The performance of the proposed controller has been found much effective to track the instantaneous reference grid voltage. The simulation work has been done with the help of MATLAB/SimPower System toolbox. This shows that the proposed controller provides effective control of voltage against the uncertain load conditions.

Gamma irradiation-induced effects on the properties of TiO_2 on fluorine-doped tin oxide prepared by atomic layer deposition

The effect of gamma irradiation with different doses(25–75 kGy) on TiO_2 thin films deposited by atomic layer deposition has been studied and characterized by X-ray diffraction(XRD),photoluminescence measurements,ultraviolet–visible(UV–Vis) spectroscopy,and impedance measurements.The XRD results for the TiO_2 films indicate an enhancement of crystallization after irradiation,which can be clearly observed from the increase in the peak intensities upon increasing the gamma irradiation doses.The UV–Vis spectra demonstrate a decrease in transmittance,and the band gap of the TiO_2 thin films decreases with an increase in the gamma irradiation doses.The Nyquist plots reveal that the overall charge-transfer resistance increases upon increasing the gamma irradiation doses.The equivalent circuit,series resistance,contact resistance,and interface capacitance are measured by simulation using Z-view software.The present work demonstrates that gamma irradiation-induced defects play a major role in the modification of thestructural,electrical,and optical properties of the TiO_2 thin films.

Successive defects asymmetric simple exclusion processes with particles of arbitrary size

This paper uses various mean-field approaches and the Monte Carlo simulation to calculate asymmetric simple exclusion processes with particles of arbitrary size in the successive defects system. In this system, the hopping probability p （p 〈 1） and the size d of particles are not constant, Through theoretical calculation and computer simulation, it obtains the exact theoretical results and finds that the theoretical results are in agreement with the computer simulation. These results are helpful in analysing the effect of traffic with different hopping probabilities p and sizes d of particle.

Method Based on Time Randomization to Resist Fault Sensitivity Analysis

A fault sensitivity analysis（FSA）-resistance model based on time randomization is proposed.The randomization unit is composed of two parts,namely the configurable register array（R-A）and the decoder（chiefly random number generator,RNG）.In this way,registers chosen can be either valid or invalid depending on the configuration information generated by the decoder.Thus,the fault sensitivity information can be confusing.Meanwhile,based on this model,a defensive scheme is designed to resist both fault sensitivity analysis（FSA）and differential power analysis（DPA）.This scheme is verified with our experiments.

A Cloud-Assisted Malware Detection and Suppression Framework for Wireless Multimedia System in IoT Based on Dynamic Differential Game

As a novel dynamic network service infrastructure, Internet of Things （IoT） has gained remarkable popularity with obvious su- periorities in the interoperability and real-time communication. Despite of the convenience in collecting information to provide the decision basis for the users, the vulnerability of embed- ded sensor nodes in multimedia devices makes the malware propagation a growing serious problem, which would harm the security of devices and their users financially and physi- cally in wireless multimedia system （WMS）. Therefore, many researches related to the mal- ware propagation and suppression have been proposed to protect the topology and system security of wireless multimedia network. In these studies, the epidemic model is of great significance to the analysis of malware prop- agation. Considering the cloud and state tran- sition of sensor nodes, a cloud-assisted model for malware detection and the dynamic differ- ential game against malware propagation are proposed in this paper. Firstly, a SVM based malware detection model is constructed with the data sharing at the security platform in the cloud. Then the number of malware-infected nodes with physical infectivity to susceptible nodes is calculated precisely based on the at- tributes of WMS transmission. Then the statetransition among WMS the modified epidemic devices is defined by model. Furthermore, a dynamic differential game and target cost function are successively derived for the Nash equilibrium between malware and WMS sys- tem. On this basis, a saddle-point malware de- tection and suppression algorithm is presented depending on the modified epidemic model and the computation of optimal strategies. Nu- merical results and comparisons show that the proposed algorithm can increase the utility of WMS efficiently and effectively.

Geospacial information utilized under the access control strategy

This paper introduces a solution to the secure requirement for digital rights management （DRM） by the way of geospacial access control named geospacial access control （GeoAC） in geospacial field. The issues of authorization for geospacial DRM are concentrated on. To geospacial DRM, one aspect is the declaration and enforcement of access rights, based on geographic aspects. To the approbation of digital geographic content, it is important to adopt online access to geodata through a special data infrastructure （SDI）. This results in the interoperability requirements on three different levels： data model level, service level and access control level. The interaction between the data model and service level can be obtained by criterions of the open geospacial consortium （OGC）, and the interaction of the access control level may be reached by declaring and enforcing access restrictions in GeoAC. Then an archetype enforcement based on GeoAC is elucidated. As one aspect of performing usage rights, the execution of access restrictions as an extension to a regular SDI is illuminated.

Efficient Activation Method of Hardware Trojan Based on Greedy Algorithm

To generate test vector sets that can efficiently activate hardware Trojans and improve probability of the hardware Trojan activation,an efficient hardware Trojan activation method is proposed based on greedy algorithm for combinatorial hardware Trojans. Based on the greedy algorithm and the recursive construction method in the combination test,the method formulates appropriate and useful greedy strategy and generates test vector sets with different combinatorial correlation coefficients to activate hardware Trojans in target circuits. The experiment was carried out based on advanced encryption standard（ AES） hardware encryption circuit,different combinatorial hardware Trojans were implanted in AES as target circuits,the experiment of detecting hardware Trojans in target circuits was performed by applying the proposed method and different combinatorial hardware Trojans in target circuits were activated successfully many times in the experiment. The experimental results showthat the test vector sets generated using the proposed method could effectively activate combinatorial hardware Trojans,improve the probability of the hardware Trojan being activated,and also be applied to practice.

Implementation of a weblog extraction system with an improved template extraction technique

Purpose: The objectives of this study are to explore an effective technique to extract information from weblogs and develop an experimental system to extract structured information as much as possible with this technique. The system will lay a foundation for evaluation, analysis, retrieval, and utilization of the extracted information.Design/methodology/approach: An improved template extraction technique was proposed.Separate templates designed for extracting blog entry titles, posts and their comments were established, and structured information was extracted online step by step. A dozen of data items, such as the entry titles, posts and their commenters and comments, the numbers of views, and the numbers of citations were extracted from eight major Chinese blog websites,including Sina, Sohu and Bokee.Findings: Results showed that the average accuracy of the experimental extraction system reached 94.6%. Because the online and multi-threading extraction technique was adopted, the speed of extraction was improved with the average speed of 15 pages per second without considering the network delay. In addition, entries posted by Ajax technology can be extracted successfully.Research limitations: As the templates need to be established in advance, this extraction technique can be effectively applied to a limited range of blog websites. In addition, the stability of the extraction templates was affected by the source code of the blog pages.Practical implications: This paper has studied and established a blog page extraction system,which can be used to extract structured data, preserve and update the data, and facilitate the collection, study and utilization of the blog resources, especially academic blog resources.Originality/value: This modified template extraction technique outperforms the Web page downloaders and the specialized blog page downloaders with structured and comprehensive data extraction.