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Background: Evaluating the risk of metastasis and recurrence of a cervical cancer patient is critical for appropriate adjuvant therapy. However, current risk assessment models usually involve the testing of tens to thousands of genes from patients’ tissue samples, which is expensive and timeconsuming. Therefore, computer-aided diagnosis and prognosis prediction based on Hematoxylin and Eosin (H&E) pathological images have received much attention recently. Objective: The prognosis of whether patients will have metastasis and recurrence can support accurate treatment for patients in advance and help reduce patient loss. It is also important for guiding treatment after surgery to be able to quickly and accurately predict the risk of metastasis and recurrence of a cervical cancer patient. Method: To address this problem, we propose a hybrid method. Transfer learning is used to extract features, and it is combined with traditional machine learning in order to analyze and determine whether patients have the risks of metastasis and recurrence. First, the proposed model retrieved relevant patches using a color-based method from H&E pathological images, which were then subjected to image preprocessing steps such as image normalization and color homogenization. Based on the labeled patched images, the Xception model with good classification performance was selected, and deep features of patched pathological images were automatically extracted with transfer learning. After that, the extracted features were combined to train a random forest model to predict the label of a new patched image. Finally, a majority voting method was developed to predict the metastasis and recurrence risk of a patient based on the predictions of patched images from the whole-slide H&E image. Results: In our experiment, the proposed model yielded an area under the receiver operating characteristic curve of 0.82 for the whole-slide image. The experimental results showed that the high-level features extracted by the deep convolutional neural network from the whole-slide image can be used to predict the risk of recurrence and metastasis after surgical resection and help identify patients who might receive additional benefit from adjuvant therapy. Conclusion: This paper explored the feasibility of predicting the risk of metastasis and recurrence from cervical cancer whole slide H&E images through deep learning and random forest methods.

BACKGROUND: Malignant lymphoma is a type of tumor that originated from the lymphohematopoietic system, with complex etiology, diverse pathological morphology, and classification. It takes a lot of time and energy for doctors to accurately determine the type of lymphoma by observing pathological images. OBJECTIVE: At present, an automatic classification technology is urgently needed to assist doctors in analyzing the type of lymphoma. METHODS: In this paper, by comparing the training results of the BP neural network and BP neural network optimized by genetic algorithm (GA-BP), adopts a deep residual neural network model (ResNet-50), with 374 lymphoma pathology images as the experimental data set. After preprocessing the dataset by image flipping, color transformation, and other data enhancement methods, the data set is input into the ResNet-50 network model, and finally classified by the softmax layer. RESULTS: The training results showed that the classification accuracy was 98.63%. By comparing the classification effect of GA-BP and BP neural network, the accuracy of the network model proposed in this paper is improved. CONCLUSIONS: The network model can provide an objective basis for doctors to diagnose lymphoma types.

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-U.S. institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection.

An efficient and accurate forest sample plot survey is of great significance to understand the current status of forest resources at the stand or regional scale and the basis of scientific forest management. Close-range photogrammetry (CRP) technology can easily and quickly collect sequence images with high overlapping to reconstruct the 3D model of forest scenes and extract the individual tree parameters automatically and, therefore, can greatly improve the efficiency of forest investigation and has great application potential in forestry visualization management. However, it has some issues in practical forestry applications. First, the imaging quality is affected by the illumination in the forest, resulting in difficulty in feature matching and low accuracy of parameter extraction. Second, the efficiency of 3D forest model reconstruction is limited under complex understory vegetation or the topographic situation in the forest. In addition, the density of point clouds by dense matching directly affects the accuracy of individual tree parameter extraction. This research collected the sequence images of sample plots of four tree species by smartphones in Gaofeng Forest Farm in Guangxi and Wangyedian Forest Farm in Mongolia to analyze the effects of image enhancement, feature detection and dense point cloud algorithms on the efficiency of 3D forest reconstruction and accuracy of individual tree parameter extraction, then proposed a strategy of 3D reconstruction and parameter extraction suitable for different forest scenes. First, we compared the image enhancement effects of median–Gaussian (MG) filtering, single-scale retinex (SSR) and multi-scale retinex (MSR) filtering algorithms. Then, an improved algorithm combining Harris corner detection with speeded-up robust features (SURF) feature detection (Harris+SURF) is proposed, and the feature matching effect is compared with that of a scale invariant feature transform (SIFT) operator. Third, according to the morphological characteristics of the trees in the sequence images, we used the iterative interpolation algorithm of a planar triangulation network based on geometric constraints (GC-based IIPTN) to increase the density of point clouds and reconstruct the 3D forest model, and then extract the position and DBH of the individual trees. The results show that MSR image enhancement can significantly increase the number of matched point pairs. The improved Harris+SURF method can reduce the reconstruction time of the 3D forest model, and the GC-based IIPTN algorithm can improve the accuracy of individual tree parameter extraction. The extracted position of the individual tree is the same as the measured position with the bias within 0.2 m. The accuracy of extracted DBH of Eucalyptus grandis, Taxus chinensis, Larix gmelinii and Pinus tabuliformis is 94%, 95%, 96% and 90%, respectively, which proves that the proposed 3D model reconstruction method based on image enhancement has great potential for tree position and DBH extraction, and also provides effective support for forest resource investigation and visualization management in the future.

The opening hotel management professional colleges in Wuhan as the research object, through the questionnaire survey to collect data, using factor analysis to build a Wuhan university hotel management professional identity evaluation system, and points out that "professional learning and industry development value", "professional teaching and influence", "study and employment", "employment intention" and "degree of learning" are the five key dimensions of professional identity. On this basis, this paper further examines the differences in the evaluation indicators of professional identity among relevant groups from the perspectives of gender, educational system and major selection, and finds that: (1) from the perspective of gender, compared with female students, male students have a higher degree of professional identity of hotel management; (2) From the perspective of educational system, there is no obvious difference in the recognition degree of the hotel management major; (3) From the perspective of major selection, compared with students who choose independently, students who are forced to change their major have a higher degree of recognition of hotel management.

The microbiota of the intestine produces a wide array of biologically active molecules and together act as a composite endocrine organ. Due to our limited understanding of bacterial communities in aquaculture ecosystems, it is necessary to evaluate the interactions between environmental and intestinal microbiota and the potential consequences of disease. This study taken the traditional P. clarkii culture in the Sichuan Basin as an example, and analyzed the relationships between the microbiota of the environment and host through microbial analysis and microbiological diagnosis. Our results showed that the bacterial abundance in sediment was greater than in water, followed by the intestine, and some of bacteria from the environment successfully selected to colonize the intestine. The bacterial composition in the intestines of diseased and healthy crayfish was significantly different. The bacteria that colonized and proliferated in the intestine had very low abundances in sediment and water. Two potential pathogens, Aeromonas veronii, and Citrobacter freundii, and two potential probiotics, Lactococcus garvieae and Exiguobacterium undae, were identified. Using multiple, real, and traditional P. clarkii aquaculture sites in the Sichuan Basin, this study revealed that the microbial communities of the environment and animal host did indeed interact. Furthermore, these results indicated that P. clarkii in a healthy status are capable of regulating which bacteria colonize their intestines.

Aims and objectives To examine the effectiveness of a nurse-led transitional care programme on readmission, self-efficacy to implement health-promoting behaviours, functional status and life quality among Chinese patients with coronary artery disease. Background Coronary artery disease is a major cause of mortality in China. Transitional care could help to ensure improved patient outcomes. Nevertheless, our knowledge of how to perform transitional care for patients with coronary artery disease is insufficient in mainland China. Design Randomised controlled trial. Methods The nurse-led transitional care intervention in the experimental group adopted the Omaha system and Pender's health-promoting model as its frameworks. The control group received a comparable length routine care and follow-up contacts. Evaluations were conducted at baseline before discharge and after 7 months after discharge using hospital readmission rate, self-rated abilities for health practices scale and Seattle Angina Questionnaire for functional status and life quality. Data were collected between March 2014-October 2014. Results Compared with the control group, participants in the experimental group showed greater self-efficacy to implement health-promoting behaviours, more angina stability, less angina frequency, more satisfaction with treatment and better quality of life. The difference in readmission rate and physical limitations was not significant between the two groups. Conclusion This study provides evidence for the effectiveness of a nurse-led transitional care programme in improving the ability to implement health-promoting behaviours, the functional status and life quality among Chinese patients with coronary artery disease. Relevance to clinical practice The nurse-led transitional care programme is helpful for coronary artery disease patients to promote their effective transfer from hospital to community and provide an evidence for nursing managers to train their nurses for transitional care knowledge and skills.

Age estimation is one of the most important components in the practice of forensic science, especially for body fluids or stains at crime scenes. Recent studies have focused on the application of DNA methylation for chronological age determination in the field of forensic genetics. However, the amount of DNA and the complex bisulfite conversion process make applying this method in trace or degraded samples difficult. MicroRNAs (miRNAs), a group of small noncoding RNAs, have great potential in forensic science due to their antidegradation property and tissue specificity. Certain miRNAs are highly age-related and may have potential utility in age prediction. In this study, the expression profile of miRNAs from blood samples was explored using massive parallel sequencing; age-related miRNAs were subsequently selected for age prediction. We then established age prediction models for bloodstains based on six age-related miRNAs using seven machine learning models. Results revealed that the mean absolute error (MAE) was 5.52 and 7.46 years in male and female bloodstain samples, respectively, using the AdaBoost algorithm. This pilot study demonstrates the possibility of performing forensic age prediction using miRNAs and may provide useful information in future case investigations.

// Mohamad Elbaz 1, 2, 5 , Dinesh Ahirwar 1, 2 , Zhang Xiaoli 3 , Xinyu Zhou 6 , Maryam Lustberg 4 , Mohd W. Nasser 1, 2 , Konstantin Shilo 1, 2 , Ramesh K. Ganju 1, 2 1 Department of Pathology, Wexner Medical Center, Ohio State University (OSU), OH, USA 2 The Comprehensive Cancer Center, Ohio State University (OSU), Wexner Medical Center, OH, USA 3 Center for Biostatistics, Ohio State University (OSU), OH, USA 4 Department of Internal Medicine, Ohio State University (OSU), OH, USA 5 Department of Pharmacology, Pharmacy School, Helwan University, Helwan, Egypt 6 Department of surgery, Davis Heart and Lung Research Institute, Ohio State University, OH, USA Correspondence to: Ramesh K. Ganju, email: Ramesh.ganju@osumc.edu Keywords: TRPV2, chemotherapy, TNBC, uptake, doxorubicin Abbreviations: Transient Receptor Potential Vanilloid type 2 (TRPV2), Triple negative Breast cancer (TNBC), Doxorubicin (Dox), CBD (cannabidiol). Received: March 24, 2016 Accepted: April 27, 2016 Published: May 27, 2016 ABSTRACT Transient receptor potential vanilloid type-2 (TRPV2) is an ion channel that is triggered by agonists like cannabidiol (CBD). Triple negative breast cancer (TNBC) is an aggressive disease with limited therapeutic options. Chemotherapy is still the first line for the treatment of TNBC patients; however, TNBC usually gains rapid resistance and unresponsiveness to chemotherapeutic drugs. In this study, we found that TRPV2 protein is highly up-regulated in TNBC tissues compared to normal breast tissues. We also observed that TNBC and estrogen receptor alpha negative (ERα - ) patients with higher TRPV2 expression have significantly higher recurrence free survival compared to patients with lower TRPV2 expression especially those who were treated with chemotherapy. In addition, we showed that TRPV2 overexpression or activation by CBD significantly increased doxorubicin (DOX) uptake and apoptosis in TNBC cells. The induction of DOX uptake was abrogated by TRPV2 blocking or downregulation. In vivo mouse model studies showed that the TNBC tumors derived from CBD+DOX treated mice have significantly reduced weight and increased apoptosis compared to those treated with CBD or DOX alone. Overall, our studies for the first time revealed that TRPV2 might be a good prognostic marker for TNBC and ERα - breast cancer patient especially for those who are treated with chemotherapy. In addition, TRPV2 activation could be a novel therapeutic strategy to enhance the uptake and efficacy of chemotherapy in TNBC patients.

Though the measurement precision of the traditional LiDAR is gradually increased, it is still limited by the quantum noise of the optical field and the extra noise introduced by the detection process. To improve the detection performance of LiDAR, a new scheme using quantum squeezed state light field as local oscillator of LiDAR was proposed and the key factors for improving the detection precision of LiDAR was analyzed. Then an integrated low-noise squeezed light field was prepared, and the experiment of LiDAR Doppler information measurement was carried out. The results show that the Doppler information detection sensitivity by using quantum squeezed state is 3 dB higher than the traditional scheme of the coherent state light field as the local oscillator, which paves a research path for the detection of weak signals such as Doppler information.

How to extract the feature information related to human body structure from image sequences and complete human motion analysis including human posture recognition is highly important research work. In this paper, an algorithm for determining the position of human joints based on human contour image features is proposed. Firstly, the virtual skeleton of the human body is extracted from the human contour using the energy function. Subsequently, the position of joints is determined based on three rules to identify whether a point in the human virtual skeleton is a joint point given in the standard human skeleton model as well as the related knowledge of human anatomy. The experimental results show that the proposed algorithm has no restrictive conditions attached to the human body in the image in the aspects of motion and color, etc. At the same time, it also has an excellent suppression effect on the noise in the human contour image. Attributing to this feature, it has a relatively low requirement for the extraction accuracy of human contour, with relatively good performance in complex backgrounds.

Background: To investigate the effectiveness of Baduanjin qigong combined with cognitive-behavior therapy (CBT) on the physical fitness and psychological health of elderly housebound. Materials and methods: The 120 elderly housebound were randomly divided into 3 intervention groups: Baduanjin training, Baduanjin training combined with CBT, and CBT. The interventions were conducted by means of home visits over 6 months. Spirometry, SF-36 health survey of quality of life, and Lawton and Brody Instrumental Activities of Daily Living Scale (IADL) were used to collect physical health data, and self-evaluation of overall health status, self-evaluation of loneliness, and short-form geriatric depression scale (GDS-15) were used to collect mental health data at baseline, 3 months, and 6 months after intervention. Data was analyzed by repeated measures analysis of variance (rANOVA) and chi-squared test (χ2 test). Results: Forced vital capacity (FVC), maximum voluntary ventilation (MVV), quality of life (QOL), and self-reported health status were significantly increased (P

With the continuously development of the HVDC transmission technology, a great number of large scale HVDC transmission projects have been completed or under construction, along with more issues come to the surface. Faults or disturbances would act on the AC/DC hybrid power grids, especially for the multi-feedback DC power grid. In this paper, the mutual influence between AC and DC grids is studied and analyzed in depth according to the actual cases. It has two aspects which conclude the impact of DC system faults on AC systems and AC system faults on DC systems separately. Theoretical analysis and research are made and specific optimization measures are proposed for how to reduce the interaction between AC and DC transmission projects after faults or disturbance in AC-DC hybrid systems.

TigerSHARC 201 link interface is a very efficient double data rate protocol. However, its inconsecutive characteristic of clock adds great difficulty for FPGA implementation when transmission rate is too high. In this paper, with specially-designed clock tree, ingenious rate decreasing strategy, plus proper control on FPGA place & routing processing, 8 group link transceivers with data rate over 500MB/s per lane were designed successfully on Xilinx Virtex6 XC6VLX130. Besides, no sophistic IOSERDES component was utilized. Whole design was completed via Verilog RTL code and Xilinx user constrained file. Presented design also has experienced harsh environment test, proved its efficiency and reliability.

Due to some limitations of traditional methods about oil temperature and level monitoring in transformer conservators, an intelligent monitoring system based on fiber Bragg grating sensors to monitor the change of oil temperature and level in transformer is proposed in this paper. This system is composed of five parts: fiber Bragg grating sensors, sensor data processing and storage, intelligent evaluation of the characteristic information of the transformer, cooperation of the monitoring and evaluation results. The oil level sensor is composed of a fiber Bragg grating sensor and a C-type spring tube, and the oil level can be monitored by the relationship between pressure and height of the liquid pressure. This method can improve the stable operation reliability of the transformer without electricity detection. The experimental results show that the central wavelength of the fiber Bragg grating sensor changes linearly with the oil temperature and level in the transformer. The intelligent monitoring system can be achieved in high voltage, electromagnetic interference and other complex environments without electricity detection, which can greatly improve the safety and reliability of the transformer.

Chronic stress is one of the major causes that lead to major depressive disorder, which is a prevalent mood disorder worldwide. Many patients with major depressive disorder do not benefit from available medication due to the complex etiology of the condition. Recently, long non-coding RNAs, molecular switches of downstream genes expression, have been reported to be involved in the pathogenesis of major depressive disorder. The long non-coding RNA TCONS_00019174 has been implicated in major depressive disorder risk and antidepressant effects, However, the effect of long non-coding RNA TCONS_00019174 on antidepressant responses has not been investigated. This study is designed to determine whether altered expression of long non-coding RNA TCONS_00019174 contributes to depression-like behaviors associated with chronic stress. We found that mice exposed to chronic ultra-mild stress displayed apparent depression-like behaviors and decreased expression of long non-coding RNA TCONS_00019174 in hippocampus. Both changed behaviors and long non-coding RNA TCONS_00019174 expression level were rescued by chronic treatment with imipramine. Viral-mediated long non-coding RNA TCONS_00019174 overexpression in hippocampal neurons improved the behaviors of mice exposed to chronic ultra-mild stress. Further, it was found long non-coding RNA TCONS_00019174 overexpression upregulated phosphorylated-GSK3$\beta$(p-GSK3$\beta$) protein and $\beta$-catenin in the hippocampus. These findings suggest that long non-coding RNA TCONS_00019174 exerts antidepressant-like effect in mice by activating a Wnt/$\beta$-catenin pathway, and that long non-coding RNA may serve as a potential therapeutic target for major depressive disorder in clinical application.

Safety engineering undergraduates in our university who are engaged in enterprise's safety management accounted for 39.38% from 2004 to 2013. To make these safety management talents more qualified for enterprise, the enterprises’ demand of capacity, quality and knowledge for safety management talents were surveyed. Questionnaire survey was conducted on 60 enterprises in various industries and safety experts in some enterprises were interviewed. Results showed that the capacity requirements were mainly the abilities of communication and coordination, organizational management, learning, and cooperation as well as English and computer skills; the quality requirements were mainly the sense of responsibility, the ideology and moral character, physical quality, proactive and hardworking spirit; the knowledge requirements were mainly safety laws and regulations, safety management and technical knowledge. Based on it, the reformation suggestions of safety management teaching in our school were put forward, such as to optimize the curriculum content, teaching method and practice teaching, aiming to cultivate students’ capability; to set up more courses, such as the humanities and social sciences, economic management, natural sciences, arts and sports to cultivate comprehensive quality; to set up more basic courses of safety management, including occupational health and safety management system, data statistics and analysis, pedagogy, psychological and behavior science to broaden the safety management theory knowledge. Furthermore, theory and practice teaching combined with safety engineering students’ employment was also stressed.

Background Coronary artery disease is a major cause of morbidity and mortality among adults worldwide, including China. After a hospital stay, transitional care could help to ensure improved patient care and outcomes, and reduce Medicare costs. Nevertheless, the results of the existing transitional care are not always satisfactory and our knowledge of how to perform effective transitional care for patients with coronary artery disease is limited in mainland China. Objectives To examine the effectiveness of a nurse-led transitional care program on clinical outcomes, health-related knowledge, and physical and mental health status among Chinese patients with coronary artery disease. Design Randomized controlled trial. Methods The Omaha system and Pender's health promoting model were employed in planning and implementing this nurse-led transitional care program. The sample was comprised of 199 Chinese patients with coronary artery disease. The experimental group (n=100) received nurse-led transitional care intervention in addition to routine care. The nurse-led transitional care intervention included a structured assessment and health education, followed by 7 months of individual teaching and coaching (home visits, telephone follow-up and group activity). The control group (n=99) received a comparable length routine care and follow-up contacts. Evaluations were conducted at baseline and completion of the interventions using the perceived knowledge scale for coronary heart disease, the medical outcomes study 36-item short-form health survey and clinical measures (blood pressure, blood glucose, lipids, body mass index). Data were collected between March and October 2014. Results Compared with the control group, participants in the experimental group showed significant better clinical outcomes (systolic blood pressure, t =5.762, P =0.000; diastolic blood pressure, t =4.250, P =0.000; fasting blood glucose, t =2.249, P =0.027; total cholesterol, t =4.362, P =0.000; triglyceride, t =3.147, P =0.002; low density lipoprotein cholesterol, t =2.399, P =0.018; and body mass index, t =3.166, P =0.002), higher knowledge scores for coronary artery disease (total knowledge score, t =−7.099, P =0.000), better physical health status ( t =−2.503, P =0.014) and mental health status ( t =−2.950, P =0.004). Conclusions This study provides evidence for the value of a nurse-led transitional care program using both the Omaha system and Pender's health promoting model as its theoretical framework. The structured interventions in this nurse-led transitional care program facilitate the use of this program in other settings.

In the spin exchange relaxation free (SERF) atomic magnetometer, it is necessary to detect an extreme small optical rotation angle. Among various methods for detecting the rotation angle, the polarization modulation technique based on a photoelastic modulator (PEM) is preferred because it features lower noise and better stability at long-time scales. However, the output signal of the photoelastic modulator contains much noise and high-order harmonics, which seriously affects the performance of the atomic magnetometer. The principle of polarization modulation technique based on photoelastic modulator and the characteristics of the detected signal were analyzed. And a dual channel digital lock-in amplifier to detect the weak signal from the atomic magnetometer was proposed. This method simplified the lock-in algorithm, reduced the complexity of the circuit and accurately detected the amplitudes of the first harmonic and the second harmonic. Theoretical analysis and simulation results show that the detection system works well and detects weak signals accurately, and the simulation error is less than 0.1%.

Studies on the occurrence of homebound and the factors influencing it are available. However, the study of community homebound in China is still in its preliminary stage. No previous studies about this issue are available. This study aims to assess the occurrence of and factors influencing homebound elderly in Chinese communities and to provide a basis for effective intervention and prevention of homebound elderly people.One sample community from three provinces was randomly selected. Investigations were performed on the selected communities and 2180 elderly people were chosen as the research subjects. Unified survey scales were used. Home visit and face-to-face interviews were performed to ensure that no single qualified survey respondent was missed.The rate of morbidity in homebound elderly Chinese community was found to be 15.49% and it gradually increased with age, and also with a lower education or poorer Activities of Daily Living (ADL). Single factor analysis showed that general situation, living habits, physical condition, mental condition, society, social support, and other factors affected the occurrence of community homebound elderly. Women were more likely to be homebound than men (P < .05). Having a spouse or high income reduced the rate of morbidity in the homebound elderly (P < .05). Multifactor regression analysis revealed that poor ADL, depression, hearing impairment, being old, no exercise, and low social support are the main influencing factors.Appropriate measures should be taken based on the specific influencing factor to prevent the occurrence of homebound.

Pico eNodeBs (PeNB) are deployed in 3GPP LTE-A networks to improve the overall performance. However, the inter cell interference may become severe without suitable coordination. In this paper, a dynamic distributed power control scheme is proposed. First, each PeNB gathers information about pico user equipments (PUE) in this cell and macro user equipments (MUE) this PeNB is interfering. Then, in power adjusted subframes, the transmit power of some resource blocks is increased while that of the others is reduced by each PeNB after throughput estimation. This process can guarantee the throughput of the PUEs and reduce the interference to MUEs in the vicinity at the same time. Simulation results show that the scheme will improve the experience of the cell edge UEs. At last, guidance is provided on how to optimally configure the parameters to achieve the potential of the scheme.

Objective To study the expressions of metallothionein and the significances in cervical squamous cell cancer (CSC), bladder transitional cell cancer (BTC), esophageal squamous cell cancer (ESC), gastral tubular adenocarcinoma (GC) and large intestinal tubular adenocarcinoma (LIC).

As people's water consumption become large and large in china, people begin to expect high requirements of water quality. However, some waterworks' monitoring system cannot automatically detect and process water quality parameters and system operation status. Therefore, staffs have to manual meter reading. The paper first discusses the design of the whole system, including the server side and the client side. It then goes on to discuss, in the server side, how to realize the communication between server and OPC client by the OPC communication technology. Finally, the paper focuses on the client side that the user interface is designed to export of automatic report and to draw the graph. Running results show that the software can detect and process parameters in real-time, and the interface is friendly, with good reliability, and can meet the demands of customers.

Objective To investigate monitoring of occupational risks factors and preventing occupational diseases. Methods A computer-based occupational disease network management system was established, namely an occupational diseases declaration and management system at work place, and collected data were analyzed by the system. Results The total number of victims contacting the occupational hazards was 13.8 million in our city, accounting for 28 % of the total number of current workers. The cumulative number of patients with occupational diseases has reached to 1,529 in the recent 5 years. Conclusion The network information management contributes to monitoring and prevention of occupational diseases, standardizing and improving the quality and efficiency of occupational diseases prevention.

Most of existing revenue sharing contract models are based on expected utility theory which is a pure rational method and assumed that all decision makers are risk-neutral or loss-neutral. The paper develops a revenue sharing contract model based on prospect theory in which decision makers in the supply chain are all loss-averse. The best order quantity of retailer, effects of retailer's loss-aversion to retailer's best order quantity, the supplier's optimal sharing proportion and trade price, and the effects of supplier's loss aversion to supplier's optimal were analyzed. It is extremely important to supply chain management decision makers.

The representation of electromagnetic situation (EMS) is a key step in spectrum management and decision support in battlefield. In the past, 2-D and 3-D visualization methods were the only options for electromagnetic environment representation, but the complexity of electromagnetic environment of modern battlefield demands for a higher level of visualization of mass-information. Thus, we propose a new method to visualize electromagnetic situation based on multi-dimension information visualization technology. To achieve this, we represent several key factors of electromagnetic field in a multi-dimensional coordinate system, and the corresponding domains are visually presented by the introduced parallel coordinates and radial coordinates. Simulation results show that this method can illustrate the electromagnetic situation in a single coordinate effectively, which could provide excellent decision supporting and planaiding for users.

Peanut is a major agronomic crop within the legume family and an important source of plant oil, proteins, vitamins, and minerals for human consumption, as well as animal feed, bioenergy, and health products. Peanut genomic research effort lags that of other legumes of economic importance, mainly due to the shortage of essential genomic infrastructure, tools, resources, and the complexity of the peanut genome. This is a pioneering study that explored the peanut Spanish Group whole plant transcriptome and culminated in developing unigenes database. The study applied modern technologies, such as, normalization and next-generation sequencing. It overall sequenced 8,308,655,800 nucleotides and generated 26,048 unigenes amongst which 12,302 were annotated and 8,817 were characterized. The remainder, 13,746 (52.77 %) unigenes, had unknown functions. These results will be applied as the reference transcriptome sequences for expanded transcriptome sequencing of the remaining three peanut botanical types (Valencia, Runner, and Virginia), which is currently in progress, RNA-seq, exome identification, and genomic markers development. It will also provide important tools and resources for other legumes and plant species genomic research.

AES encryption algorithm and digital signal processing (DSP) technology are used in image encryption transmission system to make sure the information security and confidentiality in this paper. The basic principles, structure of the algorithm and design skills are introduced and analyzed. The program design is realized in DSP environment. An overall scheme of the image encryption transmission system based on the DM642 platform is given and the DSP program design process is explained. The AES encryption running speed of image encryption transmission system in CCS environment is tested as well. Experimental results show that AES encryption algorithm and DSP technology can be applied to the real-time and secure image transmission.

In order to improve the reliability and accuracy in using ultrasonic flaw detector, this paper designed a system for detecting the flaw detector performance parameters of the transmitter, to achieve the testing and calibration of parameters for detector output characteristics of the transmitter. The core of the system is the IPC, using acquisition card PCI-5124 to collect output signal of detector's transmitter. Based on VC++, this paper designed interface of output parameters for detector's transmitter, achieved the design of driver of acquisition card better and the design of detection algorithm has various parameters. Calibration results show that: the system completed testing and calibration parameters better, such as the pulse peak, pulse rise time and duration, pulse repetition frequency, center frequency and bandwidth, the equivalent output impedance transmitter.

Objective: To investigate the difference of salivary protein mass spectrum between different traditional Chinese medicine (TCM) syndromes of thyroid cancer and establish a diagnostic model to provide an objective base for TCM syndrome of thyroid cancer. Methods: Salivary protein fingerprints of 49 thyroid cancer patients (23 cases of phlegm and blood stasis syndrome, and 26 cases of liver qi stagnation) were detected by SELDI-TOF-MS (Surface enhanced laser desorption/ionization time-of-flight mass spectrometry). And a diagnostic model was established with the help of bioinformatics. Results: Through the comparison of salivary protein fingerprints from the two groups, 29 protein peaks showed significant difference (P

Objective The salivary proteins of breast cancer patients of liver-qi stagnation syndrome and of liver-kidney yin deficiency syndrome were examined using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS), and specific protein markers were screened out to establish a salivary protein fingerprint model for distinguishing breast cancer liver-qi stagnation and liver-kidney yin deficiency. Methods The protein patterns of 47 salivary specimens (26 cases of liver-qi stagnation of breast cancer, 21 cases of liver-kidney yin deficiency of breast cancer) were examined with SELDI-TOF-MS to establish a TCM syndrome diagnosis model for breast cancer. Results 243 protein peaks were detected in the specimens, 33 of which showed significant difference between the two groups. The liver-qi stagnation syndrome and the liver-kidney yin deficiency syndrome of breast cancer could be correctly distinguished by the diagnostic model comprised of two proteins with M/Z of 8087.575 and 3378.142 Da, respectively; 25 out of the 26 cases of liver-qi stagnation syndrome was correctly diagnosed, and all the 21 cases of liver-kidney yin deficiency were correctly excluded; the sensitivity reached 96.15% (25/26) and the specificity was 80.95%(17/21). Conclusion The salivary protein fingerprint model for TCM syndrome differentiation established with SELDI-TOF-MS provided a highly specific, sensitive new method that is worth further study and application.

To explore protein expression profile in peptic ulcer saliva by proteomics mass spectrum techniques, seek for specific biomarkers of peptic ulcer diagnosis. Method Peptide mass fingerprint of saliva collected from peptic ulcer patients and healthy subjects was investigated by using MALDI-TOF-MS technique after saliva sample had been treated with WCX magnetic beads. The diagnostic cast was developed based on the peptide mass fingerprint obtained from the saliva of chronic gastritis patients and healthy subjects. Result Totally 74 protein peaks were identified from the saliva of chronic gastritis patients and healthy subjects as being associated with peptic ulcer, among which 5 specific protein peaks (P

To develop “Carbon finance” is the only way for the financial industry to go to support low carbon economy. As an emerging type of finance for environmental protection and energy conservation, carbon finance has a promising future in potential financial returns. Firstly, this paper outlines carbon finance background and carbon trading market system by analyzing the global carbon finance market structure and the domestic status in carbon finance. Finally, considering the problems in the development China's carbon finance industry, the paper proposes some strategies, hoping to help promote the right to speak of China in the field of carbon trading.

Owing to the complexity of the photovoltaic system structure and their environment, especially under the partial shadows environment, the output characteristics of photovoltaic arrays are greatly affected. Under the partial shadows environment, power-voltage (P-V) characteristics curve is of multi-peak. This makes that it is a difficult task to track the actual maximum power point. In addition, most programs are not able to get the maximum power point under these conditions. In this paper, we study the P-V curves under both uniform illumination and partial shadows environments, and then design an algorithm to track the maximum power point and select the strategy to deal with the MPPT algorithm by DSP chips and DC-DC converters. It is simple and easy to allow solar panels to maintain the best solar energy utilization resulting in increasing output at all times. Meanwhile, in order to track local peak point and improve the tracking speed, the algorithm proposed DC-DC converters operating feed-forward control scheme. Compared with the conventional controller, this controller costs much less time. This paper focuses mainly on specific processes of the algorithm, and being the follow-up basis for implementation of control strategies.

A Versatile simulation model for photovoltaic array is developed based on the DC physical model of photovoltaic (PV) module under PSIM environment. The I-V, P-V characteristics of photovoltaic array with different combina-tions can be simulated by the model. In addition, the model includes the function of Maximum Power Point Tracking (MPPT) and completes the simulation of the perturbation and observation method. It is concluded from the analysis of simulation results that high accuracy of the model simulation can accurately reflect the physical characteristics of the photovoltaic, and will provide a basis for the simulation of the power generation systems.

This paper proposes a design about sewage-source Heat Pump - Remote Monitoring System based on Web access internet configuration software. The main purpose of this design is to achieve the remote monitoring device parameters, and provide data reference for a comprehensive evaluation of technical indicators of Sewage source heat pump system. The article analyzes the process flow of sewage source heat pump system, and elaborates overall framework for remote monitoring configuration software based on Internet Web Access sewage source heat pump system, and discusses a monitoring data processing method and some system comprehensive evaluation Indicators. The design of the renewable energy heat pump system based on Web Access software, which shows that this new integration technology is very useful to reduce the consumption of traditional energy sources, improve energy efficiency.

With the development of network technology, due to the deficiencies of traditional calibration technology, a tele-calibration plan of thermocouple and resistance is presented. Combing the Data Socket with the Remote panel technology and Virtual Instrument technology, this system realizes remote temperature control, multi-channel data acquisition, video monitoring, network data transmission and remotely completes the calibration process. Experimental results show that the tele-calibration improves the efficiency of the calibration, it allows the calibration anytime and anywhere possible, transmission of data are accurate. The system provides a friendly user interface. Meanwhile, it ensures the reliability and real-time of network communication.

The paper presents a Photovoltaic (PV) Inverter System based on TMS320F28027 that can not only achieve single phase DC/AC converting by a full-bridge inverter, but also realize the function of same phase-frequency between sine waveform generated from PV Inverter System and the reference waveform from grid. Furthermore, the single phase DC/VC converting is controlled by means of SPWM generated by taking advantage of the peripheral of TMS320F28027. In addition, PV grid-connected is made up of frequency tracking and phase difference detecting, which needs TMS320F28027 to capture the frequency and calculate the phase by pulse edge detecting according to feedback circuits that can transform sine waveform into pulse waveform. Consequently, PV Inverter System can make single phase DC/VC converting and PV grid-connected come true successfully.

In order to better meet the demand of monitoring indoor environmental quality in some applications, this paper presents a scheme of design and implementation of indoor environmental monitoring system based on JN5139 SOC. The system takes full advantages of ZigBee technology of JN5139 SOC chip in wireless sensor network design and implementation to realize the hardware design of wireless sensor nodes and construct Mesh-type sensor network using JENNIC ZigBee protocol stack. Based on above design, PC monitoring control terminal is expanded so as to realize the configuration of operation mode of sensor networks and sensor nodes. The test results show that the proposed system realizes the accurate monitoring of indoor environmental quality parameters such as temperature and humidity, density of carbon dioxide.

It is very significant for urban development and urban wetland protection and utilization to probe into the process and reasons of urban wetland landscape dynamics. For a long time, the change of wetland landscape pattern has been affected by human activity, and has changed the existing wetland function. In this paper, the capital city of Beijing is for the study of wetland areas, and we used Markov Model to analysis the dynamic change and the trend evolution. Supported by RS and GIS technology, combined the achievements in previous researches and numerous field investigations, we used Landsat-TM images of 1978, 1984, 1991, 1996, 2001 and 2005. The results showed that Beijing wetland recourses degraded significantly, the patches of wetlands tended to be irregular, and the degree of fragmentation was increasing, thus the wetland would be easy to cause regression, and its function was difficult to exert; The transition probability matrices at two primary states were established. Then, the development and the future tendency of wetland landscape patterns were simulated and forecasted with Markov process. In the existing humanity affects, Beijing wetland landscape pattern may achieve a relative stable state. The findings have provided the basis for sustainable development and the scientific management of Beijing wetland.

During the process of enterprises implementing independent innovation, intellectual property risk will be induced by a variety of uncertain events. So this paper analyzes the influence of Knowledge management capability to intellectual property risk through 218 questionnaires with SEM, the main contributions can be summarized as follows: the capability of knowledge conersion, knowledge application and knowledge protection can effectively reduce the intellectual property risk which independent innovation enterprise faced. To the enterprise, design of organization mechanism, application of information technology can promote knowledge management, in order to avoid facing the intellectual property risk which is caused by all kinds of omissions on the knowledge management at the greatest degree. The orientation of further research are proposed at last.