Effect of b value on monitoring therapeutic response by diffusion-weighted imaging

AIM： To explore the diffusion gradient b-factor that optimizes both apparent diffusion coefficient （ADC） measurement and contrast-to-noise （CNR） for assessing tumor response to transarterial chemoembolization （TACE） in a rabbit model. METHODS： Twelve New Zealand white rabbits bearing VX2 tumors in the liver were treated with TACE. Diffusion-weighted imaging （DWI） with various b values was performed using the same protocol before and 3 d after treatment with TACE. ADC values and CNR of each tumor pre- and post-treatment with different b factors were analyzed. Correlation between ADC values and extent of necrosis in histological specimens was analyzed by a Pearson＇s correlation test.RESULTS： The quality of diffusion-weighted images diminished as the b value increased. A substantial decrease in the mean lesion-to-liver CNR was observed on both pre- and post-treatment DW images, the largest difference in CNR pre- and post-treatment was manifested at a b value of 1000 s/mm^2 （P = 0.036 ）. The effect of therapy on diffusion early after treatment was shown by a significant increase in ADCs （P = 0.007）, especially with large b factors （≥ 600 s/mm^2）. The mean percentage of necrotic cells present within the tumor was 76.3%-97.5%. A significant positive correlation was found between ADC values and the extent of necrosis with all b values except for b200, a higher relative coefficient between ADC values and percentage of necrosis was found on DWI with bl000 and b2000 （P = 0.002 and 0.006, respectively）. CONCLUSION： An increasing b value of up to 600 s/mm^2 would increase ADC contrast pre- and post-treatment, but decrease image quality. Taking into account both CNR and ADC measurement, diffusion-weighted imaging obtained with a b value of 1000 s/mm^2 is recommended for monitoring early hepatic tumor response to TACE.

RVFLN-based online adaptive semi-supervised learning algorithm with application to product quality estimation of industrial processes

Direct online measurement on product quality of industrial processes is difficult to be realized,which leads to a large number of unlabeled samples in modeling data.Therefore,it needs to employ semi-supervised learning(SSL)method to establish the soft sensor model of product quality.Considering the slow time-varying characteristic of industrial processes,the model parameters should be updated smoothly.According to this characteristic,this paper proposes an online adaptive semi-supervised learning algorithm based on random vector functional link network(RVFLN),denoted as OAS-RVFLN.By introducing a L2-fusion term that can be seen a weight deviation constraint,the proposed algorithm unifies the offline and online learning,and achieves smoothness of model parameter update.Empirical evaluations both on benchmark testing functions and datasets reveal that the proposed OAS-RVFLN can outperform the conventional methods in learning speed and accuracy.Finally,the OAS-RVFLN is applied to the coal dense medium separation process in coal industry to estimate the ash content of coal product,which further verifies its effectiveness and potential of industrial application.

Design of nuclear radiation level gauge based on normalized LMS filtering correction

In the measurement of liquid level in industrial site environment,noise interference can affect the measurement accuracy.In order to improve the measurement accuracy of liquid level in the viscous state,a nuclear radiation level measurement system based on the least mean square(LMS)filtering correction method is designed.The system uses STM32F103 as the control core and adopts HART bus HT1200M chip for remote signal transmission and reception.The adaptive LMS algorithm can be used for more accurate filtering,calculating iterative weight vector,updating weighted coefficient,effectively removing system measurement noise and improving the measurement accuracy.The results show that the nuclear radiation level gauge based on normalized LMS can correct the measurement system accuracy in adaptive rules,improve the measurement accuracy to meet the requirements of industrial field environment for liquid level measurement and enhance the industrial automation control degree.

A Master-Slave Blockchain Paradigm and Application in Digital Rights Management

Upon flaws of current blockchain platforms of heavyweight, large capacity of ledger, and time-consuming of synchronization of data, in this paper, we proposed a new paradigm of master-slave blockchain scheme(MSB) for pervasive computing that suitable for general PC, mobile device such as smart phones or PADs to participants in the working of mining and verification, in which we separated traditional blockchain model in 2 layer defined as master node layer and a series of slavery agents layer, then we proposed 2 approaches for partially computing model(PCM) and non-computing of model(NCM) in the MSB blockchain, Finally large amounts of simulations manifest the proposed master-slave blockchain scheme is feasible, extendible and suitable for pervasive computing especially in the 5 G generation environment, and can apply in the DRM-related applications.

Application of whole body diffusion weighted imaging in bone metastasis

Objective： We evaluated （Whole-Body Diffusion Weighted Imaging, WB-DWl） application in bone metastasis. Methods： WB-DWI with GE 1.5T MR/I was performed on 10 healthy volunteers and 35 patients. WB-DWl and ECT was performed in all 35 patients. Using WB-DWl for detecting bone metastasis and compared them with that of ECT. Results： Background was suppressed in WB-DWl, fat, muscle, vessels and liver appeared same as background. Skeleton showed medium or slightly lower signal. Lymph nodes, some glandular organs, kidneys displayed medium signal. Spleen, testicle, brain tissue were low signal. Bladder, gallbladder were depicted as low signal because of ＂T2 through＂. Bone metastasis were multitude and inequality of size, punctiform, nodosity, column low intensity. Concordance between WB-DWI and ECT was seen in 4 cases. WB-DWl displayed 1 bone metastasis on skull, 46 on rib and sternum, 3 on scapula, 4 on extremities, 83 on vertebral, 36 on pelvic bone. ECT showed 2 bone metastasis on skull, 62 on rib and sternum, 7 on scapula, 9 on extremities, 64 on vertebral, 19 on pelvic bone. WB-DWl was 74% for bone metastasis on rib and sternum, ECT was 77%, 53% for vertebral and pelvic bone. All of the focus were statistics analyses, P 〈 0.05. Total probability distribution inequality if metastasis on different positions. Conclusion： WB-DWI was an effective imaging technology for screening bone metastasis.

Pyramidal Edge Detection Method Based on AWFM Filtering and Fuzzy Linking Model

A novel multiresolution pyramidal edge detector, based on adaptive weighted fuzzy mean(AWFM)filtering and fuzzy linking model, is presented in this paper. The algorithm first constructs a pyramidal structure by repetitive AWFM filtering and subsampling of original image. Then it utilizes multiple heuristic linking criteria between the edge nodes of two adjacent levels and considers the linkage as a fuzzy model, which is trained offline. Through this fuzzy linking model, the boundaries detected at coarse resolution are propagated and refined to the bottom level from the coarse-to fine edge detection. The validation experiment results demonstrate that the proposed approach has superior performance compared with standard fixed resolution detector andprevious multiresolution approach, especially in impulse noise environment.

Study on gas monitoring technology based on information fusion

In view of the deficiency of current gas monitoring systems in coal mine roadwayexcavation, a two-level information fusion technology, which adopted the adaptiveweighted algorithm and the BP neural network technology, was applied to gas monitoring.The results show that the adaptive weighted algorithm can realize self-regulation by decreasingthe weight value of the failed sensor automatically, so as to eliminate the effect ofthe failed sensor and ensure the effectiveness and accuracy of the gas monitoring system.The BP neural network can not only effectively predict the gas gush quantity of the excavationroadway, but also accurately calculate the gas concentration in the region whereone or more sensors have failed, so as to provide the basis for judging the safety status ofthe roadway excavation.The experiments prove the superiority and feasibility of the applicationof information fusion in gas monitoring.

On Effective Virtual Networks Interconnection

The network services today require extremely agile and mobile, however, the traditional IP infrastructures are so rigid that cannot fit services well. A way should be put forward to automate the network to improve responsiveness to change. SDN and network virtualization(NV) are two hottest approaches to make networking more automated and scalable to support virtualized and cloud environments. Network virtualization combines hardware and software network resources and network functionality into a single virtual network. SDN is created to simplify traffic management and achieve operational efficiencies by establish and exercising central control over packet forwarding. In this paper, we focus on the situation where SDN controller needs to connect two virtual networks temporarily. We put forward three algorithms to try to make this connection more effective and evaluate these three algorithms.

Modified Adaptive Weighted Averaging Filtering Algorithm for Noisy Image Sequences

In order to avoid the influence of noise variance on the filtering performances, a modified adaptive weighted averaging (MAWA) filtering algorithm is proposed for noisy image sequences. Based upon adaptive weighted averaging pixel values in consecutive frames, this algorithm achieves the filtering goal by assigning smaller weights to the pixels with inappropriate estimated motion trajectory for noise. It only utilizes the intensity of pixels to suppress noise and accordingly is independent of noise variance. To evaluate the performance of the proposed filtering algorithm, its mean square error and percentage of preserved edge points were compared with those of traditional adaptive weighted averaging and non-adaptive mean filtering algorithms under different noise variances. Relevant results show that the MAWA filtering algorithm can preserve image structures and edges under motion after attenuating noise, and thus may be used in image sequence filtering.

Application of Tradable Emission Permits in Europe

The purpose of this study is merely to review the current situation in the designing and implementation of the emission trading programs in Europe. Historical data show that although there is a series of shortcomings in their current functioning, employing such instruments for GHG reduction policy making is strongly expected to be efficient and effective. The European Union Emission Trading Scheme (EU ETS), Clean Development Mechanism (CDM) and Joint Implementation (JI) are just a few examples of the ambitious EU initiative that heavily relies on such instruments. We dwell on their operations and achievements by far and all the content in this article is expected to convince the Chinese government and regional public authorities to take positive actions and attitudes in promoting these instruments.

Adaptive Gaussian Noise Image Removal Algorithm Using Filtering-Based Noise Estimation

This paper proposes a spatially denoising algorithm using filtering-based noise estimation for an image corrupted by Gaussian noise.The proposed algorithm consists of two stages:estimation and elimination of noise density.To adaptively deal with variety of the noise amount,a noisy input image is firstly filtered by a lowpass filter.Standard deviation of the noise is computed from different images between the noisy input and its filtered image.In addition,a modified Gaussian noise removal filter based on the local statistics such as local weighted mean,local weighted activity and local maximum is used to control the degree of noise suppression.Experiments show the effectiveness of the proposed algorithm.

Seasoned Equity Offerings and " Herd Behavior " of Earnings Management

A model to explain the dynamic characters of earnings management was developed based on the interactionamong several firms’ disclosure policies. Under the condition of incomplete information, each firm’s earnings man-agement will be influenced by the earnings disclosure policies of other firms. It can lead to "herd behavior" of earningsmanagement. This paper studies the relationship between earnings manipulation and rights issue policy based on thedistribution of earnings after management. The results indicate that Chinese listed companies trend towards controllingROE in the narrow ranges just above 6% and 10% .Therefore, "herd behavior" exists in the earnings management.

An improved adaptive response surface method for structural reliability analysis

The response surface method(RSM) is one of the main approaches for analyzing reliability problems with implicit performance functions.An improved adaptive RSM based on uniform design(UD) and double weighted regression(DWR) was presented.In the proposed method,the basic principle of the iteratively adaptive response surface method is applied.Uniform design is used to sample the fitting points.And a double weighted regression system considering the distances from the fitting points to the limit state surface and to the estimated design points is set to determine the coefficients of the response surface model.Compared with the conventional approaches,the fitting points selected by UD are more representative,and a better approximation in the key region is also observed with DWR.Numerical examples show that the proposed method has good convergent capability and computational accuracy.

Trade-off Optimization for Scalable Video Coding Streaming in Relay-Based OFDMA Networks

To achieve an optimal trade-off between video quality and energy efficiency in the uplink streaming of multi-user Scalable Video Coding (SVC) videos in relay-based Orthogonal Frequency Division Multiple Access (OFDMA) cellular networks, a cross-layer design framework that jointly selects the Transmission Policy (TP) for SVC video frames, assigns OFDMA subcarriers, and allocates power for each subcarrier is proposed. We apply the dual decomposition method to the problem, and obtain a TP selection subproblem for each SVC video adaptation and a resource allocation subproblem of Joint Subcarrier, Relay and Power Allocation (JSRPA). A second level of dual decomposition is used to divide the JSRPA problem into independent subcarrier subproblems. The proposed Crosslayer Trade-off Optimization (CTO) algorithm is sub-distributed with significantly low complexity. A performance evaluation with typical SVC video traces demonstrates that the proposed algorithm is able to converge and efficiently achieve the optimal trade-off between the video quality and energy consumption at the MSs for uplink SVC streaming.

＂Principal Components＂ for the Calculation of the Best Estimate Liability of Future Discretionary Benefits under Solvency II

The core of the presentation that I propose treats about the application of principal component analysis for the estimation of the future earnings of the Segregated Funds. The Segregated Funds are the pools of assets which have been using in the Italian Insurance Market since mid 80＇s for managing the ＂with profit＂ business, also known as business with ＂discretionary participation feature＂ according to IFRS4 since the income attributable to the policyholders is composed by the net realised gains less a fee and by a minimum guarantee, if any. The discretion of the Management of the Entity lays on the decision on whether and when to realise both the financial gains and the financial losses of the underlying investments. This strategy is tied by the need to manage an appropriate ALM, from the rules included in the local legislation as well as by the policy about the solvency margin （for example a minimum solvency ratio to fulfil that is conditional upon the value of income attributed that year）. The fee can not be changed, i.e., is not discretionary, the minimum granted could be fixed on annual basis-sometimes paid on cash recurrently-or could be promised only at expiration or sometimes promised at expiration or in advance only for death and disability. In case of years so adverse that the Entity is not able to avoid earnings too low, sometimes the entity delivers an additional bonus, in order to compensate their policyholders, which is based above a full discretion. Principal components are used in finance as well as in other fields such as genetic. You can see some of these applications in two of the references advised below. The purposes of the technique of principal components are （1） to increase objectivity of results and their verifiability by third parties such as auditors, （2） make speeder the time spent for the analytical calculations （i.e., runs of the actuarial models） and （3） to render the relationship between the asset composition and the their earnings effectively used for the best estimate liabilities through their contribution in forecasting future cash flows.

Model Modification and Application on Carrying Capacity of Relative Resources

Based on the retrospection of researches on carrying capacity, this article reviewed systematically the research progresses on carrying capacity of relative resources (CCRR). Then the viewpoint was put forward that CCRR is not an appropriate method of appraising the regional sustainability, but a sound way to obtain cognition for coordinating spatial location and flow of population and economy. However, as the most popular computing method of CCRR, the Weighting Linear Sum Model is defective in the random of weight choice and the neglect of matching among different resources. Therefore, this article established the Geometric Model on CCRR based on modifying Weighting Linear Sum Model, which can be used to appraise regions where resources are close matching. Employing the Geometric Model, the article empirically analyzed the population and economic CCRR in Hubei Province from 1978 to 2006. The result indicates that the population in Hubei Province is overloading while the economic carrying capacity is abundant compared to the whole country, and the economic insufficiency restricts the population carrying capacity. In the future, Hubei Province will become one of the core developing zones which are characterized by economic conglomeration.

Pereira＇s Equity： Teaching Introductory Accounting With a Family Approach

The case describes the situation of a Brazilian accounting courses in undergraduate programmes middle-class family, as an alternative to teach introductory In its solution, it was used an accounting system, adapted to the needs of register, control, and information of the family equity, through the application of the content of introductory accounting. The authors aim to offer a didactic and playful alternative for the teaching of introductory accounting in undergraduation courses, such as business management, accountancy, economy, and others in which this course is offered. The aim is to show the integration of accounting contents offered in the course, applied to the most common and nearest experience of freshmen in their first year during the undergraduate program： the family. The case can be solved in two phases： In the first, during a class of up to 100 minutes, the professor develops six activities, culminating in the students answering up to four suggested questions; in the second, whose application is left to the professor, in another class further ahead, is numerical.

Application of Bit Error Rate Information Based on Weighted Error Estimating Code

Error Estimating Code (EEC) is a new channel coding method to estimate the Bit Error Rate (BER) information of the transmitted sequence. However, the estimated BER is not precise enough if the practical value of BER is high. A weighted EEC estimation method is proposed to improve the accuracy performance of BER estimation by classifying the raw estimation results into intervals and multiplying them by different coefficients separately. The applications of weighted EEC in modulation selection scheme and distributed video coding are discussed. Simulation results show that the EEC-based modulation selection method can achieve better performance at a cost of little redundancy and computation, and the EEC-based rate estimation method in distributed video coding can save the decoding time.

ADRs and Children： Knowledge and Methodological Standard in PASS （Post Authorization Safety Studies）

PhV （pharmacovigilance） knowledge has the outcome of being inadequate in particular due to the lack of instruction. Pediatricians have to face the realization that over-the-counter medicines increments the peril of ADRs （adverse drug reactions） has become a public health concern. The purpose of this article is to disseminate knowledge of the PhV and to highlight the cultural and organizational difficulties for its implementation. The objectives of promoting the organization of specific training courses and research projects aimed at： （1） to foster the culture of iatrogenic disease in pediatrics; （2） to improve the appropriateness of prescribing drugs in children; （3） to enco.urage spontaneous reporting of ADRs in children; （4） to involve Pediatricians in PASS （post-authorization safety studies） according to GCP, GVP and ENCEPP Code of Conduct. An up to date proposal of PhV, a procedure of preparation improves the productivity of creating novel informative reports which can be utilized for a benefit/risk scrutiny making strides in medicine prescription. In this context, FP-MCRN （family paediatficians-medicines for children research network） established with the aim of developing competence, infrastructure and education for paediatric clinical trials, plays a crucial role in paediatric PhV, through an improvement of PhV training, a correct research methodology and very strong relationship with the families. The initial necessity is cultural, implementing culture of iatrogenic illnesses and a watchful evaluation of the importance of PASS by FPs （family pediatricians）. Participation in clinical trials that generates a precise database administered by FPs together with follow-up outcomes becomes relevant and vital for a scrupulous and accurate assessment of ADRs. PASS can foresee on one hand training and information regarding the proper use of drugs in children and possible iatrogenic pathologies caused by their improper use, the other to constitute a territorial survey in the prescriptive appropriateness and safety of pediatric drugs aimed at evaluating the risk-benefit balance on usage.

Novel Adaptive Weighted Mean Filter

Based on the advantages and disadvantages of the standard median filter and the standard wean filter, a new Adaptive Weighted Mean Filter（AWFM） was proposed in this paper. The filter window＇s size of every pixel was adaptively adjusted. Then the suspidons noise points were examined by certain rules. After that, the authors calculate the weighting factors of the pixels by weighting function which was canstructed according to the differences between their gray values and the median value of all elements in the window. Finally they use the weighted average of gray values to substitute the gray value of the central pixel in the window. The results indicate that this filtering method is not only effective for impulse noise like median filter, but also better than the standard median filters. Compared with conventional filter, this filter methed can effectivdy suppress the mixture noise of images, and protect image＇s details well.