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A giant fusiform aneurysm of the middle cerebral artery is a disease that causes many difficulties for endovascular intervention as well as surgery. No 1 solution is optimal for all cases, however for post-bifurcation aneurysms, trapping the aneurysms with a reanastomosis reimplantation, an in situ side to side bypass is feasible and has good results. We reported a 28-year-old male patient, admitted to the hospital because of severe headache, Glasgow Coma Scale 13 points, left hemiplegia, was diagnosed with subarachnoid hemorrhage due to rupture of a giant fusiform aneurysm of the middle cerebral artery in the M2 segment, Hunt and Hess grade 4. The patient underwent microsurgery with clipping aneurysm combined with a low-flow technique connecting the superficial temporal artery to the middle cerebral artery. Our findings suggest that surgery to connect the superficial temporal artery to the M2 segment and at the same time obstructing the parent artery occlusion of selected giant MCA aneurysm is an option to consider.

Enhancing EFL learners’ communicative competence is a time-taking process to reach certain levels of interacting with different communication participants. However, in the tertiary education in Vietnam, traditional teaching approach with the task-based learning does not thoroughly focus on the language use but on the strategies to perform the tasks. Hence, the functional approach has been applied to boost learners’ awareness of their language delivery thanks to communicative functions and notions. The new mode of teaching concentrates on what communication participants desire to convey and why they make use of those speech acts. This paper aimed to explore the impact of the integration of task-based learning and the functional approach, and learners’ perspective towards the implementation of such approach combination. With the application of the mixed method of qualitative and quantitative approaches, the data were collected via a pre-test and a post-test, survey, and 32 interviews with the participation of 100 students whose major is Business Administration at a university. The findings reveal that adding the functional approach to the existing teaching method could enhance students’ overall speaking competence, especially their fluency and discourse management. Additionally, the application of the functional approach received positive feedback from the learners.

The purpose of this paper is to investigate the determinants of the Operational Self-Sustainability (OSS) of Vietnamese microfinance institutions (MFIs). This research uses both qualitative and quantitative research methods: (i) qualitative research was via in-depth interviews with ten microfinance practitioners, policymakers and researchers; (ii) quantitative research was conducted by using panel data of 34 MFIs in the period 2011-2015 with binary logistics and OLS regressions. Results are as follows: (i) MFIs’ OSS in Vietnam are mainly determined by five key factors: portfolio at risk (PAR>30), capital structure, gross loan portfolio, scope of activities and legal form; (ii) OSS are most affected by legal status (social organizations have better OSS than formal MFIs or programs/projects), location (MFIs focus in one province have higher OSS than working nationwide or just in one district), capital structure (MFIs with more equity proportion have higher OSS); (iii) surprisingly, average loan size per borrower and age of MFIs do not have statistically significant correlation with OSS. The key recommendations are: (i) MFIs should focus on its professionality and increase its equity; (ii) related stakeholders such as State Bank of Vietnam should promote the enabling ecosystem for microfinance development to enhance poverty reduction and economic development.

The field of English translation and interpretation has shown an increasing popularity in Vietnam in the context of globalization. However, translation in the target culture still has a certain number of problems in transferring the equivalence between two languages, which causes some ambiguities and misunderstandings for readers (House, 2015). Hence, translation quality assurance is significant in ensuring the degree of suitability of the texts as a post-translation process (Munday, 2016). This paper aimed to investigate the difficulties of English majors of translation and interpretation in assessing the quality of texts translated from English to Vietnamese during the learning process on an independent basis. The study employed the mixed method with 50 fourth-year students at Nguyen Tat Thanh University via questionnaires. The findings revealed that those majors had to deal with five main groups of troubles including (1) time constraints, (2) non-equivalence between English and Vietnamese, (3) insufficient cultural understandings, (4) inadequate supports from lecturers, and especially (5) the lack of official framework for translation quality assessment. This paper also proposes the fundamental for university curriculum developments from the learners’ perspectives.

Maintaining the rotational speed of synchronous generators in a hydropower plant is a vital control strategy in power system stability and operation. It is because such rotational speed is proportional to the output frequency of the synchronous generator, thereby it strongly affects the stability of the electric power grid. This paper presents a study regarding the modelling and control of a hydropower plant to maintain the generator speed. This study is divided into two main parts. A well-used model of an isolated hydropower plant is established in this study at first; then two controllers including conventional PI and intelligent fuzzy logic regulators are investigated to speed control of the generator. Simulations implemented in MATLAB/Simulink package demonstrate effectiveness and feasibility of the proposed speed controllers.

The research is taken to integrate the effects of variable selection approaches, as well as sampling techniques, to the performance of a model to predict the financial distress for companies whose stocks are traded on securities exchanges of Vietnam. A firm is financially distressed when its stocks are delisted as requirement from Vietnam Stock Exchange because of making a loss in 3 consecutive years or having accumulated a loss greater than the company’s equity. There are 12 models, constructed differently in feature selection methods, sampling techniques, and classifiers. The feature selection methods are factor analysis and F-score selection, while 3 sets of data samples are chosen by choice-based method with different percentages of financially distressed firms. In terms of classifying technique, logistic regression together with SVM are used in these models. Data are collected from listed firms in Vietnam from 2009 to 2017 for 1, 2 and 3 years before the announcement of their delisting requirement. The experiment’s results highlight the outperformance of the SVM model with F-score selection method in a data sample containing the highest percentage of non-financially distressed firms.

BACKGROUND: Thrombectomy is recommended to treat for an acute ischemic stroke (AIS) patient with anterior large vessel occlusion. However, there were neither detailed guidelines nor systematic reviews of acute ischemic stroke patients having multiple times or re-occluded arteries. CASE REPORT: In our case report, we struggled a multiple (4-times) AIS patient underwent by one intravenous r-tpA and 3 remaining of endovascular treatment of thrombectomy. Especially, the finding of both pulmonary embolism and cerebral arteries occlusion in this patient made us difficult to decide the appropriate treatment plan. The patient was considered having multiple cardiac thrombi pumping out to the brain and pulmonary vessels even in treatment with NOAC (New Oral Anticoagulant). Our priority, normally, was to recanalize the brain vessels compared to the pulmonary arteries. CONCLUSION: In conclusion, based on this noticed case study, we want to share our experiences on the diagnosis of ischemic stroke, the strategy in treatment and prevention with anticoagulant therapy.

One-dimensional zinc oxide (ZnO) nanorods have excellent electron mobility and exhibit great potential for photoelectric or photochemical applications. However, poor visible light absorption and rapid surface charge recombination are bottleneck for promoting its applications. In this work, plasmonic gold nanoparticles (Au NPs) and dielectric silicon oxide (SiO2) are deposited on the surface of ZnO nanorods to tune their photoelectric performance. The localized surface plasmon resonance of Au NPs extends the absorption spectrum to visible region. The surface passivation with dielectric SiO2 layer suppresses the photoexcited electron-hole recombination. By rational integration of the configuration, it is found that dielectric spacer (ZnO-SiO2-Au) shows obvious photocurrent improvement. While dielectric shell-coating (ZnO-Au-SiO2) dramatically leads to an outstanding photocurrent enhancement, which is ∼4–28 times higher than that of the other counterparts. The enhanced performance is ascribed to its effectiveness for spatially separating electron-hole pairs and optimizing photo-absorption properties of the metal-semiconductor system. This strategy provides new insights into fabrication of high performance light harvesting antenna, and stands for a basis to design solar-active systems.

Background: To date, the role of bridging intravenous thrombolysis before mechanical thrombectomy (MTE) is controversial but still recommended in eligible patients. Different doses of intravenous alteplase have been used for treating patients with acute ischemic stroke from large-vessel occlusion (LVO-AIS) in Asia, largely due to variations in the risks for intracerebral hemorrhage (ICH) and treatment affordability. Uncertainty exists over the potential benefits of treating low-dose alteplase, as opposed to standard-dose alteplase, prior to MTE among patients with LVO-AIS.Aim: The aim of the study was to compare outcomes of low- vs. standard-dose of bridging intravenous alteplase before MTE among LVO-AIS patients.Methods: We performed a retrospective analysis of LVO-AIS patients who were treated with either 0.6 mg/kg or 0.9 mg/kg alteplase prior to MTE at a stroke center in Northern Vietnam. Multivariable logistic regression models, accounting for potential confounding factors including comorbidities and clinical factors (e.g., stroke severity), were used to compare the outcomes between the two groups. Our primary outcome was functional independence at 90 days following stroke (modified Rankin score; mRS ≤ 2). Secondary outcomes included any ICH incidence, early neurological improvement, recanalization rate, and 90-day mortality.Results: We analyzed data of 107 patients receiving bridging therapy, including 73 with low-dose and 34 with standard-dose alteplase before MTE. There were no statistically significant differences between the two groups in functional independence at 90 days (adjusted OR 1.02, 95% CI 0.29–3.52) after accounting for potential confounding factors. Compared to the standard-dose group, patients with low-dose alteplase before MTE had similar rates of successful recanalization, early neurological improvement, 90-day mortality, and ICH complications.Conclusion: In the present study, patients with low-dose alteplase before MTE were found to achieve comparable clinical outcomes compared to those receiving standard-dose alteplase bridging with MTE. The findings suggest potential benefits of low-dose alteplase in bridging therapy for Asian populations, but this needs to be confirmed by further clinical trials.

This paper presents a low-power power management IC (PMIC) for Thermal Electric Generator (TEG) applications that includes investigation, demonstration, and comparison between two hybrid DC-DC converters. Both converters employs an input inductive step-up stage and an output switched-capacitor stage. The first converter, a 2-stage boost converter (2SBC), has a Boost stage connected in series with a switched-capacitor doubler, fully integrated with all control and regulation circuits. The second converter is an open-loop three-level boost converter (3LBC). Both converters are designed in a single prototype chip, fabricated in a 180-nm process. The PMIC’s self-start operation is verified at a minimum voltage of 50mV. The functionality of both converters are verified to match with simulation results, achieving above 50% efficiency for a wide range of loads. The peak efficiencies of 65% and 83% are achieved for the 2-stage boost converter and the three level boost converter at 150mV and 180mV input voltages, respectively.

Given that the one-size-fits-all approach to mobile health interventions have limited effects, a personalized approach might be necessary to promote healthy behaviors and prevent chronic conditions. Our systematic review aims to evaluate the effectiveness of personalized mobile interventions on lifestyle behaviors (i.e., physical activity, diet, smoking and alcohol consumption), and identify the effective key features of such interventions. We included any experimental trials that tested a personalized mobile app or fitness tracker and reported any lifestyle behavior measures. We conducted a narrative synthesis for all studies, and a meta-analysis of randomized controlled trials. Thirty-nine articles describing 31 interventions were included (n = 77,243, 64% women). All interventions personalized content and rarely personalized other features. Source of data included system-captured (12 interventions), user-reported (11 interventions) or both (8 interventions). The meta-analysis showed a moderate positive effect on lifestyle behavior outcomes (standardized difference in means [SDM] 0.663, 95% CI 0.228 to 1.10). A meta-regression model including source of data found that interventions that used system-captured data for personalization were associated with higher effectiveness than those that used user-reported data (SDM 1.48, 95% CI 0.76 to 2.19). In summary, the field is in its infancy, with preliminary evidence of the potential efficacy of personalization in improving lifestyle behaviors. Source of data for personalization might be important in determining intervention effectiveness. To fully exploit the potential of personalization, future high-quality studies should investigate the integration of multiple data from different sources and include personalized features other than content.

ObjectiveTo determine the effectiveness of physical activity interventions involving mobile applications (apps) or trackers with automated and continuous self-monitoring and feedback.DesignSystematic review and meta-analysis.Data sourcesPubMed and seven additional databases, from 2007 to 2020.Study selectionRandomised controlled trials in adults (18–65 years old) without chronic illness, testing a mobile app or an activity tracker, with any comparison, where the main outcome was a physical activity measure. Independent screening was conducted.Data extraction and synthesisWe conducted random effects meta-analysis and all effect sizes were transformed into standardised difference in means (SDM). We conducted exploratory metaregression with continuous and discrete moderators identified as statistically significant in subgroup analyses.Main outcome measuresPhysical activity: daily step counts, min/week of moderate-to-vigorous physical activity, weekly days exercised, min/week of total physical activity, metabolic equivalents.ResultsThirty-five studies met inclusion criteria and 28 were included in the meta-analysis (n=7454 participants, 28% women). The meta-analysis showed a small-to-moderate positive effect on physical activity measures (SDM 0.350, 95% CI 0.236 to 0.465, I2=69%, T2=0.051) corresponding to 1850 steps per day (95% CI 1247 to 2457). Interventions including text-messaging and personalisation features were significantly more effective in subgroup analyses and metaregression.ConclusionInterventions using apps or trackers seem to be effective in promoting physical activity. Longer studies are needed to assess the impact of different intervention components on long-term engagement and effectiveness.

Alzheimer's Disease (AD) is known as a degenerative neurological progression that causes the loss of neurons and synapses in the cerebral cortex. The cognitive functions are gradually impaired over several to 20 years and no current cure. It is crucial for timely conversion prediction to AD in its earliest phrase. In this study, we propose a novel recurrent neural network (RNN) model to obtain biomarkers of brain and clinical diagnosis of each subject from only one to indefinitely forecast the biomarkers and clinical diagnosis at each timepoint in the future. However, unexpected missing observations is a common issue in longitudinal data. Moreover, in recurrent dynamical systems, gates should be closer to 1 to propagate more information from earlier time steps to later ones. Two strategies are explored to handle missing data and improve gating mechanisms in recurrent neural network to boost performance. Empirically, our gating mechanisms robustly improve the performance when longitudinal data is utilized. On the baseline dataset from The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) challenge, our proposal outperforms the conventional recurrent neural network in term of multi-class Area Under Curve (mAUC) which achieving 0.79734 ± 0.01785.

In recent years, deep learning has dominated medical image segmentation. Encoder-decoder architectures, such as U-Net, can be used in state-of-the-art models with powerful designs that are achieved by implementing skip connections that propagate local information from an encoder path to a decoder path to retrieve detailed spatial information lost by pooling operations. Despite their effectiveness for segmentation, these na&iuml, ve skip connections still have some disadvantages. First, multi-scale skip connections tend to use unnecessary information and computational sources, where likable low-level encoder features are repeatedly used at multiple scales. Second, the contextual information of the low-level encoder feature is insufficient, leading to poor performance for pixel-wise recognition when concatenating with the corresponding high-level decoder feature. In this study, we propose a novel spatial-channel attention gate that addresses the limitations of plain skip connections. This can be easily integrated into an encoder-decoder network to effectively improve the performance of the image segmentation task. Comprehensive results reveal that our spatial-channel attention gate remarkably enhances the segmentation capability of the U-Net architecture with a minimal computational overhead added. The experimental results show that our proposed method outperforms the conventional deep networks in term of Dice score, which achieves 71.72%.

The foundations of nuclear medicine in Vietnam were established from 1970. Until now, after 48 years of development, in Vietnam, we have some basic equipment including 31 SPECT, 4 SPECT/CT machines, 11 PET/CT scanners, five cyclotrons, and one nuclear reactor. Many nuclear medicine techniques in diagnosis and treatment have been routinely performed at provincial and central level health facilities such as tumor scintigraphy, thyroid scintigraphy, bone scintigraphy, kidney scintigraphy, cardiac scintigraphy, and radio-isotope therapy with I-131 and P-32. Selective internal radiation therapy with Y-90 microsphere and I-125 radioactive seed implantation has been also successfully applied in some big hospitals. However, there are still many difficulties for Vietnam as the lack of new widely used radioisotopes such as Ga-67, Cu-64, Samarium-153, and Lutetium-177 and the lack of nuclear medicine specialists. In the future, we are putting our efforts on the applications of new isotopes in diagnosis and treatment of cancers (theranostic) like Ga-68-DOTATATE, Lutetium-177-DOTATATE, Ga-68-PSMA, and Lutetium-177-PSMA, equipping modern nuclear medicine diagnostic tools, strengthening the human resources training in nuclear medicine. At the same time, we are trying our best to strengthen the cooperation with international nuclear medicine societies in over the world.

Objective: to evaluate predictors the risk of symptomatic intracerebral heamorrhage after thrombolytic therapy with recombinant tissue plasminogen activator in acute ischemic stroke. Methods: observative study on 54 patients with acute ischemic stroke at Emergency Department, Bach Mai hospital from 01/2010 to 10/2016. Results: Predictors the risk of symptomatic intracerebral heamorrhage were: age above 70 (OR 2,76; 95% CI 0,73 – 10,52; p = 0,12), time from onset to treatment (OR 1,03; 95% CI 0,34 – 3,13; p = 0,95), systolic blood pressure ≥ 140 mmHg (OR 2,0; 95% CI 0,61 – 6,51; p = 0,24), NIHSS score above 12 (OR 3,13; 95% CI 0,63 – 15,51; p = 0,138), glycemia above 10 mmol/l (OR 8,94; 95% CI 1,51 – 51,73; p = 0,003), fibrillation atrial (OR 1,49; 95% 0,49 – 4,56; p = 0,33), history of diebete (OR 6,4; 95% CI 0,67 – 61,03; p = 0,06), history of anticoagulation (OR 1,07; 95% CI 0,22 – 5,11; p = 0,63), history of cerebral infarction (OR 1,49; 95% CI 0,183 – 12,184; p = 0,707), sign of early brain CT (OR 6,14; 95% CI 1,01 – 39,93; p = 0,048). Conclusion: glucose above 10 mmol/l and sign of early brain CT were predictors the risk of symptomatic intracerebral heamorrhage after thrombolytic therapy with recombinant tissue plasminogen activator in acute ischemic stroke. Key words: stroke, thrombolysis, predictor, heamorrhage conversion

Purpose: Recombinant tissue plasminogen activator (rtPA) activity may be enhanced with ultrasound, 2 MHz transcranial Doppler (TCD). We performed the trial to determine the efficacy of ultrasound-enhanced thrombolysis compared to the current standard of care (intravenous rtPA). Subjects and methods: We treated 80 patients who had acute ischemic stroke due to occlusion of the middle cerebral artery with intravenous rtPA within 4.5 hours after the onset of symptoms. The patients were randomly assigned to receive continuous 2-MHz transcranial Doppler ultrasonography (the target group) or placebo (the control group). The primary combined end point was complete recanalization as assessed by transcranial Doppler ultrasonography and dramatic clinical recovery at 2 hours. Complete recanalization was defined as thrombolysis in brain ischemia (TIBI) flow grades 4-5. Secondary end points included recovery at 24 hours, a favorable outcome at three months. Results: A total of 80 patients were randomly assigned to receive continuous ultrasonography (40 patients) or placebo (40 patients). Complete recanalization and dramatic clinical recovery within two hours after the administration of a rtPA bolus occurred in 13 patients in the target group (32,5%), as compared with 8 patients in the control group (20%) (P=0.038). At three months, 22 patients in the target group who were eligible for follow-up analysis (55%) and 13 in the control group (32,5%) had favorable outcomes (as indicated by a score of 0 to 1 on the modified Rankin scale) (P=0.012). Intracerebral hemorrhage occurred in five patients in the target group and in four in the control group. Conclusion: In patients with acute ischemic stroke due to occlusion of the middle cerebral artery, continuous transcranial Doppler augments rtPA-induced arterial recanalization, with an increased rate of recovery from stroke, as compared with placebo. Continuous 2-MHz transcranial Doppler ultrasonography for 2 hours is safe. Key words: Stroke, transcranial Doppler, tissue plasminogen activator

BACKGROUND: The cerebral arterial aneurysm, especially in the circumstances of ateriovenous malformation (AVM), has higher risk of rupture than normal isolated aneursym. Therefore, the treatment strategy needs to be plan very carefully in such case. CASE PRESENTATION: We report a patient with 2 wide-neck aneurysms located in the feeding artery of the arteriovenous malformation and he, then, was treated by using Surpass stent (flow-diverter) to eliminate the aneurysms. CONCLUSION: In our case, multiple wide-neck aneurysms in combination with low risk unruptured AVM, using long Surpass stent-diversion is an effective way to eliminate all the aneurysms in the main feeding artery while still preserving the AVM anatomy.

In this paper, we aim to develop an effective combining algorithm for ensemble learning systems. The Decision Template method, one of the most popular combining algorithms for ensemble systems, does not perform well when working on certain datasets like those having imbalanced data. Moreover, point estimation by computing the average value on the outputs of base classifiers in the Decision Template method is sometimes not a good representation, especially for skewed datasets. Here we propose to search for an optimal decision template in the combining algorithm for a heterogeneous ensemble. To do this, we first generate the base classifier by training the pre-selected learning algorithms on the given training set. The meta-data of the training set is then generated via cross validation. Using the Artificial Bee Colony algorithm, we search for the optimal template that minimizes the empirical 0–1 loss function on the training set. The class label is assigned to the unlabeled sample based on the maximum of the similarity between the optimal decision template and the sample’s meta-data. Experiments conducted on the UCI datasets demonstrated the superiority of the proposed method over several benchmark algorithms.

The focus of this work is to design a novel hybrid load-frequency control (LFC) strategy for a multi-area large-scale electric power interconnection. The proposed methodology is based on two consecutive control phases, including an artificial neural network model and a PD-like fuzzy logic inference system. The new two-stage architecture enables this control strategy to utilize the advantage of each phase, and thus it is able to enhance the robustness of the LFC controller to quickly restore the steady state of the network after load variations. In addition, superconducting magnetic energy storage (SMES) devices, which can powerfully compensate for the loss of energy in an electric power grid, are investigated to support the LFC scheme. The integration of the novel hybrid LFC controller and the SMES devices in a large-scale network is completely capable of being a promising control solution for maintaining the system frequency against the load variations. The feasibility and superiority of the proposed control strategy over the conventional PI regulators as well as a number of previous studies will be demonstrated through numerical simulation processes with various load conditions implemented in a six-control-area electric power interconnection.

—Maintaining the network frequency at its nominal value due to the load changes is one of the most important issues in the control and operation schedule of a large and multi-area interconnected power system. For the effective control solution, two types of tie-line bias control strategy-based controllers have been applied, i.e., classical and improved controllers. The classical controllers using conventional regulators, including integral, proportional–integral and proportional-integral-derivative, have achieved initial control results to bring the steady state back to the network. However, due to the very poor control features (e.g., large overshoots and long settling times), they need to be replaced with improved controllers, such as fuzzy logic and artificial neural network. To obtain an entire evaluation of the application of different load-frequency controllers, a five-control-area interconnected power system was built as a typical case study. Three improved controllers using proportional-pl...

Load-frequency control (LFC) strategy aims to extinguish oscillations of both the frequency and tie-line power deviations to restore the steady state of an electric grid after load change occurs. Classical controllers, e.g., Proportional–Integral (PI) regulators, have been initially applied to deal with the LFC. However, the main control performances, such as overshoots and settling times, should be further optimized to maintain the frequency within the desired tolerances. This paper investigates a novel approach using two-stage controllers based on neural network and fuzzy logic technique to improve efficiently the control performances. A six-control-area-interconnected power system model is also built as the typical case study. Subsequently, the proposed controllers will be applied to this model to solve the LFC issue in two cases: with and without using superconducting magnetic energy storage (SMES) devices. In principle, such SMES units can compensate efficiently load variations in a power sys...

In this paper, the design of 3 intelligent control strategies applying fuzzy logic (FL) and articial neural network (ANN) techniques is investigated to deal with network frequency maintenance against load variations in a large- scale multiarea interconnected power system. These intelligent frequency controllers proposed in this study include FL-PI, ANN-NARMA(nonlin autoregressive moving average)-L2, and ANN-RMC (reference model control). In principle, they are designed depending upon the tie-line bias control method, which has been applied efficiently for damping frequency oscillations. A mathematical model of an n-control-area interconnected power system with different generation units is builtrst to apply the control methodologies in order to maintain the grid frequency at its nominal value (50 Hz or 60 Hz). Such a model is considered to be typical candidate of a complicated large-scale power system in reality. Numerical simulation with various cases of load conditions are also implemented in this study using the MATLAB/Simulink package to demonstrate the feasibility and effectiveness of the proposed control strategies. It is found that the 3 intelligent controllers presented in this paper are capable of achieving superiority over the conventional integral regulators in system frequency stabilization. The main dynamic control indexes obtained, especially the overshoot and settling time, are highly promising to effectively extinguish the dynamic responses of the frequency and tie-line power deviations. Thus, the steady state of the power network can be restored more quickly after load variation occurrence. In that way, the stability, reliability, and economy of an electric power grid are able to be guaranteed effectively.

Modern and large power systems, which are normally composed of several interconnected generating stations (multiarea), have complex and diverse structures in practice. It is necessary to deal with the automatic generation control to ensure the stability, continuity, and economy of the generation schedule in a power grid. For the automatic generation control strategy, the most important goal is to protect the network frequency from load variations, which can appear randomly in any area. As a result, it is essential to design efficient controllers applied to multiarea interconnected power systems in order to maintain the network frequency at the nominal values (50 Hz or 60 Hz), and keep the tie-line power ow at the scheduled MW. In this paper, werst analyze and build a model of the 6-control-area interconnected power system as the typical case study. Subsequently, different frequency controllers based on tie-line bias control strategy, namely integral, proportional{int proportional{int , and PI-based fuzzy logic, will be investigated and applied to the power system model. The most important control performances, such as overshoots and settling times, are considered in this study to evaluate the stability of the power system and choose the most suitable controller for maintaining the network frequency. The simulation results have been achieved by using MATLAB/Simulink package version 2013 in this work. According to these results, the maximum overshoots of the PI-based fuzzy logic controller are from 36.56% to 90.13%, and its settling times are from 19.00% to 98.26% in comparison with the other regulators in the given control power system. Therefore, the PI-based fuzzy logic controller has been chosen as the best control solution to bring the grid frequency back to its nominal value as quickly as possible after occurrence of load variations.

To the Editor: Revolutionizing the traditional Systematic Evolution of Ligands by EXponential Enrichment (SELEX), high-throughput SELEX (HT-SELEX) has become the method of choice for the identification of aptamers—synthetic, single-stranded (ribo)nucleic molecules that bind to a given molecular target.1 In contrast to traditional SELEX, in which only data from the last selection cycle is obtained, HT-SELEX allows for sequencing of every round (including control cycles) which are then jointly analyzed and interpreted.

SUMMARY A small but growing proportion of patients requiring radiotherapy for prostate cancer have one or two hip prostheses which may shadow the target and affect the dose distribution. Approximately 10 such patients are treated at the Illawarra Cancer Care Centre per year. Hence a study was undertaken to examine the accuracy of various treatment methods that involve some of the treatment fields travelling through the prosthesis. A fixed-field measurement showed a dose reduction of 52% in the shadow of the prosthesis. A Monte Carlo simulation confirmed an increase in dose on the distal surface of the prosthesis of 35%. Of more clinical relevance, however, is the dose distribution due to the overall combined field treatment. Using a power law correction benchmarked against thermoluminescent dosimeters and Gafchromic film, three different beam set-ups for patient treatment were planned and the dose variation analysed. A four-field brick technique gave a dose variation across the target volume of ± 15% whereas a dual arc technique gave a dose variation of only ± 5%. A four-field oblique technique gave a dose variation of only ± 2% across the target volume but the oblique field technique included extra dose to the rectum.

Purpose: Due to the limitations of fine-needle aspiration biopsy (FNAB) cytopathology, many individuals who present with thyroid nodules eventually undergo thyroid surgery to diagnose thyroid cancer. The objective of this study was to use whole-transcriptome profiling to develop and validate a genomic classifier that significantly improves the accuracy of preoperative thyroid cancer diagnosis. Materials and Methods: Nucleic acids were extracted and amplified for microarray expression analysis on the Affymetrix Human Exon 1.0 ST GeneChips from 1-mm-diameter formalin-fixed and paraffin-embedded thyroid tumor tissue cores. A training group of 60 thyroidectomy specimens (30 cancers and 30 benign lesions) were used to assess differential expression and for subsequent generation of a genomic classifier. The classifier was validated in a blinded fashion on a group of 31 formalin-fixed and paraffin-embedded thyroid FNAB specimens. Results: Expression profiles of the 57 thyroidectomy training and 31 FNAB validation specimens that passed a series of quality control steps were analyzed. A genomic classifier composed of 249 markers that corresponded to 154 genes, had an overall validated accuracy of 90.0% in the 31 patient FNAB specimens and had positive and negative predictive values of 100% and 85.7%, respectively. The majority of the identified markers that made up the classifier represented non-protein-encoding RNAs. Conclusions: Whole-transcriptome profiling of thyroid nodule surgical specimens allowed for the development of a genomic classifier that improved the accuracy of preoperative thyroid cancer FNAB diagnosis.

A current major challenge in systems biology is to compute statistics on biomolecular network motifs, since this can reveal significant systemic differences between organisms. We extend the "color coding" technique to weighted edge networks and apply it to PPI networks where edges are weighted by probabilistic confidence scores, as provided by the STRING database. This is a substantial improvement over the previously available studies on, still heavily noisy, binary-edge-weight data. Following up on such a study, we compute the expected number of occurrences of non-induced subtrees with k ≤ 9 vertices. Beyond the previously reported differences between unicellular and multicellular organisms, we reveal major differences between prokaryotes and unicellular eukaryotes. This establishes, for the first time on a statistically sound data basis, that evolutionary distance can be monitored in terms of elevated systemic arrangements.

The P2X(7) receptor is a ligand-gated channel that is highly expressed on mononuclear cells and that mediates ATP-induced apoptosis of these cells. Wide variations in the function of the P2X(7) receptor have been observed, in part because of a loss-of-function polymorphism that changes Glu-496 to Ala without affecting the surface expression of the receptor on lymphocytes. In this study a second polymorphism (Ile-568 to Asn) has been found in heterozygous dosage in three of 85 normal subjects and in three of 45 patients with chronic lymphocytic leukemia. P2X(7) function was measured by ATP-induced fluxes of Rb(+), Ba(2+), and ethidium(+) into various lymphocyte subsets and was decreased to values of approximately 25% of normal. The expression of the P2X(7) receptor on lymphocytes was approximately half that of normal values as measured by the binding of fluorescein-conjugated monoclonal antibody. Transfection experiments showed that P2X(7) carrying the Ile-568 to Asn mutation was non-functional because of the failure of cell surface expression. The differentiation of monocytes to macrophages with interferon-gamma up-regulated P2X(7) function in cells heterozygous for the Ile-568 to Asn mutation to a value around 50% of normal. These data identify a second loss-of-function polymorphism within the P2X(7) receptor and show that Ile-568 is critical to the trafficking domain, which we have shown to lie between residues 551 and 581.

In this paper, we present our continued effort in the development of broadband spatial power combining systems implemented in a standard WR-90 waveguide environment. With sixteen commercial MMIC amplifiers integrated with tapered-slot antenna arrays, a new combining circuit renders a 61-watt maximum power output and a gain variation less than /spl plusmn/1.4 dB within the entire band of interest. Higher output power can be achieved by introducing more MMIC amplifiers but still maintaining the same circuit topology, thanks to the modular design of the spatial combiner.

We report a case of B-cell chronic lymphocytic leukemia in a 58 year old female in whom the clinical course was dominated by upper airway obstruction due to massive enlargement of the palatine and later the lingual tonsils. The peripheral blood morphology and immunophenotype were typical of chronic lymphocytic leukaemia with expression of CD 19+, CD20+, CDS+, CD23+ and HLA-DR+ together with weak, surface immunoglobulin with monoclonal lambda light chain. Therapy included surgical removal of the palatine tonsils and later chemotherapy, both of which provided temporary relief of obstruction before recurrence of obstruction at the site of the lingual tonsils. Lasting relief from mass effect and obstruction only occurred following localised radiotherapy to Waldeyer's ring.