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Elephant flow (elephant) classification is significant for network performance management and resource optimization. Classifying elephants over Software Defined Networks (SDNs) often relies on statistics counted by switches and transferred to controllers, leading to a huge control channel bandwidth occupation that degrades network latency and user experience. Classifying elephants using flow packets forwarded to controllers completely avoids moving statistics from switches to controllers, but couples flow entry timeouts to elephant classification accuracy, time efficiency, flow table size, control channel bandwidth usage, and network latency. This paper aims to find the best flow entry timeouts to optimize the objectives by modeling the objectives and formulating a multi-objective optimization problem. The number of objectives is further reduced to 3 and the problem is solved by Machine Learning (ML) approaches. Extensive evaluations are made over real packet traces. To the best of our knowledge, this work is the first effort that explores all the objectives related to flow entry timeouts when using flow packets forwarded to controllers to classify elephants over SDNs. &nbsp

Regulatory B cells (Bregs) are immune cells that constrain autoimmune response and restrict inflammation via their expression of interleukin (IL)-10. However, the molecular mechanisms underlying Breg differentiation and IL-10 secretion remain unclear. Previous data suggest that cellular metabolism determines both the fate and function of these cells. Here, we suggest an essential role for mitochondrial oxidative phosphorylation (OXPHOS) in the regulation of IL-10 in these Bregs. We found that IL-10

Inflammatory bowel diseases (IBDs) are prevalent and debilitating diseases with limited clinical treatment strategies. Mesenchymal stem cells (MSCs) are pluripotent stem cells with self-renewal capability and multiple immunomodulatory effects, which make them a promising therapeutic approach for IBDs. Thus, optimization of MSC regimes is crucial for their further clinical application. Wogonin, a flavonoid-like compound with extensive immunomodulatory and adjuvant effects, has been investigated as a potential pretreatment for MSCs in IBD treatment. This research aimed to compare the therapeutic effectiveness of MSCs pretreated with or without wogonin. Compared to untreated MSCs, MSCwogonin (pretreated with wogonin) showed greater effectiveness in the treatment of colitis. Further experiments revealed that wogonin treatment activated the AKT signaling pathway, resulting in higher cellular glycolysis. Inhibition of AKT phosphorylation by perifosine not only decreased glycolysis but impaired the therapeutic efficiency of MSCwogonin. Consistent with these results, qPCR data indicated that wogonin treatment induced the expression of immunomodulatory molecules IL-10, IDO, and AGR1, which were reduced by perifosine. Together, our data demonstrated that wogonin preconditioning strategy further augmented the therapeutic efficacy of MSCs via promoting glycolysis, which should be a promising strategy for optimizing MSC therapy in IBDs.

Purpose This study aimed to evaluate the safety and efficacy of chimeric antigen receptor (CAR) disialoganglioside 2 (GD2)-specific (4SCAR-GD2) T cells for treatment of refractory and/or recurrent neuroblastoma (NB) in pediatric patients. Experimental design A phase I clinical study using 4SCAR-GD2 T cells for the treatment of NB in pediatric patients was conducted. This study was registered at www.clinicaltrials.gov (NCT02765243). A lentiviral CAR with the signaling domains of CD28/4-1BB/CD3ζ-iCasp9 was transduced into activated T cells. The response to 4SCAR-GD2 T-cell treatment, and 4SCAR-GD2 T-cell expansion and persistence in patients were evaluated. Toxicities were determined based on the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) v4.03. Results Twelve patients were enrolled and finally ten patients were included in this clinical trial which started from January 1, 2016, to August 1, 2017. These patients had progressive disease (PD) before CAR T-cell infusion. After 4SCAR-GD2 T-cell treatment, 6 (6/10) had stable disease (SD) at 6 months, and 4 (4/10) remained SD at 1 year and alive after 3–4 years of follow-up. Six patients died due to disease progression by the end of July 1, 2020. The median overall survival (OS) time was 25 months (95% CI, 0.00–59.43), and the median progression-free survival (PFS) time was 8 months (95% CI, 0.25–15.75). Grade 3 or 4 hematological toxicities were the common adverse events frequently occurred after fludarabine and cyclophosphamide (Flu/cy) chemotherapy. Grade 1–2 toxicities such as cytokine release syndrome (CRS) and neuropathic pain were common, but were transient and mild. Conclusions The 4SCAR-GD2 T-cell therapy demonstrated antitumor effect and manageable toxicities, indicating its potential to benefit children with refractory and/or recurrent NB.

Background The proto-oncogene c-MET (mesenchymal-epithelial transition factor gene) plays a critical role in cellular proliferation, survival, migration, and invasion in cancers. The aim of this study is to explore the relationship between c-MET expression and the clinicopathological characteristics of colorectal cancer (CRC) patients. Methods A total of 337 enrolled patients were collected in present study. Here, the c-MET and EGFR expression were detected by immunohistochemistry (IHC). The mutational statuses of KRAS in exons 2, 3, and 4, NRAS in exons 2, 3, and 4, and BRAF in exon 15 from formalin-fixed sections were detected by direct DNA sequencing. Results Our results showed that high c-MET expression was significantly associated with tumor perineural invasion (P=0.007) and gender (P=0.016). High level c-MET expression (c-MET-high) in the primary tumors was observed in 68.2% of patients. In the 337 enrolled patients, 43.2% of patients had KRAS mutations, 3.3% of patients had NRAS mutations, and 4.7% of patients had BRAF mutations. However, KRAS, NRAS, and BRAF gene mutations had no association with c-MET protein levels in primary tumors. Additionally, c-MET protein expression had a strong correlation with EGFR expression (P=0.002). The survival time was not significantly longer for patients with c-MET-high primary tumors than for those with c-MET-low primary tumors. Conclusions c-MET immunohistochemistry was significantly higher in primary tumors with perineural invasion, female gender, and EGFR high expression. However, c-MET-high in the primary tumors was not significantly associated with longer survival compared with c-MET-low tumors. Further studies are required to investigate c-MET as potential molecular marker of progression and to test the possibility of its incorporation as a new therapeutic target.

Colon cancer (CC) is the third most commonly diagnosed malignant tumor and remains the second leading cause of cancer-related deaths worldwide. However, the risk assessment of poor prognosis of CC is limited in previous studies. This study aimed to develop a predictive nomogram for the survival of CC patients.In this retrospective cohort study, 113,239 CC patients from the Surveillance, Epidemiology, and End Results (SEER) database were randomly divided into training (n=56,619) and testing (n=56,620) sets with a ratio of 1:1. Demographic, clinical data and survival status of patients were extracted. The outcomes were 3- and 5-year survival of CC. Univariate and multivariate Cox regression analyses were used to screen the predictors to develop the predictive nomogram. Internal validation and stratified analyses were further assessed the nomogram. The C-index and area under the curve (AUC) were calculated to estimate the model's predictive capacity, and calibration curves were adopted to estimate the model fit.Totally 38,522 (34.02%) patients died during the 5-year follow-up. The nomogram incorporated variables associated with the prognosis of CC patients, including age, gender, marital status, insurance status, tumor grade, stage (T/N/M), surgery, and number of nodes examined, with a C-index of 0.775 in the training set and 0.774 in the testing set. The AUCs of the nomogram for the 3- and 5-year survival prediction in the training set were 0.817 and 0.808, with the sensitivity of 0.688 and 0.716, and the specificity of 0.785 and 0.740, respectively. Similar results were found in the testing set. The C-index of the predictive nomogram for male, female, White, Black, and other races was 0.769, 0.779, 0.773, 0.770, and 0.770, respectively. The calibration curves for the nomogram in the above five cohorts showed a good agreement between actual and predicted values.The nomogram may exhibit a certain predictive performance based on the SEER database, which may provide individual survival predictions for CC patients.

OBJECTIVE: The purpose of this study was to compare the safety and efficacy of ultrasound and fluoroscopy-guided for determining the puncture entry point of percutaneous vertebroplasty (PVP). Methods: From November 2018 to December 2019, a total of 50 eligible patients with thoracolumbar osteoporotic vertebral compression fractures (OVCFs) treated by PVP were retrospectively collected, of which 25 cases were in ultrasound-guided group and the other 25 cases were in fluoroscopy-guided group. Radiation doses, one-time localization success rate, operation time, clinical efficacy and complications incidence were compared between the two groups. Results: Ultimately, 46 patients completed followed-up, whose average follow-up time was 9 months, the dose and times of fluoroscopy and operation time in ultrasound-guided group statically significantly decreased compared with fluoroscopy-guided group (P0.05). There were no postoperative complications such as infection, hematoma formation and fracture nonunion observed between the two groups.Conclusion: Ultrasound-guided entry point determination for PVP puncture is safe, which can significantly improve the success rate of one-time localization and decrease radiation exposure and operation time.

The aim is to explore the predictive value of salivary bacteria for the presence of esophageal squamous cell carcinoma (ESCC). Saliva samples were obtained from 178 patients with ESCC and 101 healthy controls, and allocated to screening and verification cohorts, respectively. In the screening phase, after saliva DNA was extracted, 16S rRNA V4 regions of salivary bacteria were amplified by polymerase chain reaction (PCR) with high-throughput sequencing. Highly expressed target bacteria were screened by Operational Taxonomic Units clustering, species annotation and microbial diversity assessment. In the verification phase, the expression levels of target bacteria identified in the screening phase were verified by absolute quantitative PCR (Q-PCR). Receiver operating characteristic (ROC) curves were plotted to investigate the predictive value of target salivary bacteria. LEfSe analysis revealed higher proportions of Fusobacterium, Streptococcus and Porphyromonas, and Q-PCR assay showed significantly higher numbers of Streptococcus salivarius, Fusobacterium nucleatum and Porphyromonas gingivalis in patients with ESCC, when compared with healthy controls (all P

Objective: The purpose of this study was to compare the safety and efficacy of ultrasound and fluoroscopy-guided for determining the puncture entry point of percutaneous vertebroplasty (PVP). Methods: From November 2018 to December 2019, a total of 50 eligible patients with thoracolumbar osteoporotic vertebral compression fractures (OVCFs) treated by PVP were retrospectively collected, of which 25 cases were in ultrasound-guided group and the other 25 cases were in fluoroscopy-guided group. Radiation doses, one-time localization success rate, operation time, clinical efficacy and complications incidence were compared between the two groups.Results: Ultimately, 46 patients completed followed-up, whose average follow-up time was 9 months, the dose and times of fluoroscopy and operation time in ultrasound-guided group statically significantly decreased compared to fluoroscopy-guided group (Px2= 4.33, P=0.037), whose difference was statistically significant (P0.05). There were no postoperative complications such as infection, hematoma formation and fracture nonunion obsereved between the two groups.Conclusion: Ultrasound-guided entry point determination for PVP puncture is safe, which can significantly improve the success rate of one-time localization and decrease radiation exposure and operation time.

Supplementary_tables for Upregulation of DAB2IP Inhibits Ras Activity and Tumorigenesis in Human Pancreatic Cancer Cells by Yifan Duan, Xiaoyu Yin, Xiaorong Lai, Chao Liu, Wenjing Nie, Dongfeng Li, Zijun Xie, Zijun Li and Fan Meng in Technology in Cancer Research & Treatment

Federated learning (FL) is a type of distributed machine learning approacs that trains global models through the collaboration of participants. It protects data privacy as participants only contribute local models instead of sharing private local data. However, the performance of FL highly relies on the number of participants and their contributions. When applying FL over conventional computer networks, attracting more participants, encouraging participants to contribute more local resources, and enabling efficient and effective collaboration among participants become very challenging. As software-defined networks (SDNs) enable open and flexible networking architecture with separate control and data planes, SDNs provide standardized protocols and specifications to enable fine-grained collaborations among devices. Applying FL approaches over SDNs can take use such advantages to address challenges. A SDN control plane can have multiple controllers organized in layers; the controllers in the lower layer can be placed in the network edge to deal with the asymmetries in the attached switches and hosts, and the controller in the upper layer can supervise the whole network centrally and globally. Applying FL in SDNs with a layered-distributed control plane may be able to protect the data privacy of each participant while improving collaboration among participants to produce higher-quality models over asymmetric networks. Accordingly, this paper aims to make a comprehensive survey on the related mechanisms and solutions that enable FL in SDNs. It highlights three major challenges, an incentive mechanism, privacy and security, and model aggregation, which affect the quality and quantity of participants, the security and privacy in model transferring, and the performance of the global model, respectively. The state of the art in mechanisms and solutions that can be applied to address such challenges in the current literature are categorized based on the challenges they face, followed by suggestions of future research directions. To the best of our knowledge, this work is the first effort in surveying the state of the art in combining FL with SDNs.

To investigate the correlation of KRAS gene mutation and surgery for clinical characteristics and prognosis in patients with colorectal cancer under a 5-year follow-up, clinical data of 277 patients with colorectal cancer treated from January 2010 to December 2010 were collected. Patients with KRAS gene mutation were detected by direct sequencing and followed up for 5 years. KRAS gene mutation effect on clinicopathological factors and univariate and multivariate survival were analyzed. Among 277 patients, 109 (39.8%) indicated KRAS gene exon 2 mutation, among which 12 colon mutations showed the highest frequency. Furthermore, KRAS gene mutation was revealed to have a correlation with the expression of EGFR, primary tumor site, and multiple metastases of tumor. In follow-up, the average survival time of patients carrying wild-type and mutant-type was 49.9 months and 50.7 months, respectively. Univariate analysis showed that high TNM stage, advanced age, pulmonary metastasis, hepatic metastasis, and multiple metastases were associated with poor postoperative prognosis in patients with colorectal cancer. Multivariate analysis showed that advanced age and high TNM stage were independent risk factors for postoperative outcome in patients with colorectal cancer. The median OS in IV patients after surgery still reached 39.6 months, and some patients survived. In conclusion, KRAS gene mutation in colorectal cancer patients is closely related to EGFR expression, primary tumor site and multiple metastasis, and the survival time of advanced patients is prolonged.

Designing urban rail transit systems is a complex problem, which involves the determination of station locations, track geometry, and various other system characteristics. Most of the previous rail transit route optimization studies have focused on the alignment design between predetermined stations, whereas a practical design process has to account for the complex interactions among railway alignments and station locations. This paper proposes a methodology for concurrently optimizing station locations and the rail transit alignment connecting those stations, by accommodating multiple system objectives, satisfying various design constraints, and integrating the analysis models with a geographical information system database. The methodology incorporates demand and station costs in the evaluation framework and employs a genetic algorithm for optimizing the decision variables for station locations, station types, and track alignments. It is expected that transit planners may greatly benefit from the proposed methodology, with which they can conveniently and efficiently optimize candidate alternatives. The Baltimore Red Line is used as a case study to demonstrate how the model can find very good solutions in regions with complex geography.

e16033 Background: Apatinib, a selective vascular endothelial growth factor receptor-2 (VEGFR2) inhibitor, has demonstrated encouraging anticancer activity across a broad range of malignancies. Recent studies have shown efficacy of apatinib as a third-line treatment for patients with refractory colorectal cancer. In this study, we characterized the genomic profile and explored predictive and prognostic biomarkers in metastatic colorectal cancer (mCRC) patients treated with apatinib as the 3rd line treatment. Methods: We retrospectively recruited 19 mCRC patients, with a median age of 53, treated with apatinib as the third-line regimen. The cohort consisted of 10 female and 9 male patients with 13 and 6 patietns with left-seide and right-sided CRC, respectively. Tissue samples prior to apatinib treatment were profiled using a 520-cancer-related gene panel. Results: This cohort achieved an ORR of 16% (3/19) and DCR of 53% (10/19). The median PFS and OS were 5 and 8.7 months, respectively, comparable with published studies. The genomic profile of 19 patients showed that 57% of alterations were missense, and 18% and 12% were copy number variations (CNV) and frameshift, respectively. All 19 patients were microsatellite stable (MSS). Most frequently mutated genes were TP53 (95%), APC (53%) and KRAS (53%). Other commonly mutated genes included PI3KCA (26%), FAT3 (16%), LPR1B (16%), FLT1(16%), SAMD4 (16%), TCF7L2 (16%) and TCNNB1 (16%). Univariate Cox analysis revealed a shorter PFS in patients harboring FLT1 amplification (n = 3) versus those without (P = 0.0007). All 3 patients with FLT1 amplification had progressive diease as their best response, with an average PFS of 1.4 months. Furthermore, we also revealed that APC mutation was significantly associated with older age (P = 0.02) and lymph node metastasis (P = 0.01). Patients with pulmonary metastasis were more likely to have TP53 disruptive mutation (P = 0.02). Conclusions: Our study explored the potential predictive biomerkers for apatinib and revealed that FLT1 amplification might be a potential predictive biomarker for poor efficacy in mCRC patients treated with apatinib. FLT1 encodes VEGFR1, which could compete with VEGFR2 for binding with VEGF, potentially explaining the inferior response to apatinib observed in pateints harboring FLT1 amplification. Larger cohorts are needed to validate the finding.

KRAS mutation-induced Ras activation plays an important role in the pathogenesis of pancreatic cancer, but the role of wild-type Ras and Ras GTPase-activating proteins remains unclear. The present study was designed to determine the expression spectra of Ras GTPase-activating proteins genes in pancreatic cancer cells, and the role of DAB2IP, a Ras GTPase-activating proteins gene, in the development and progression of pancreatic cancer. Following the analyses of the expression profiles of 16 Ras GTPase-activating proteins in 6 pancreatic cancer cell lines including Bxpc-3 (with wild-type KRAS), Capan-2, Sw1990, Aspc-1, CFPAC-1, and Panc-1 (with mutant KRAS) and 1 normal human pancreatic ductal epithelial cell line, H6C7, the expression of DAB2IP messenger RNA was further analyzed by quantitative real-time polymerase chain reaction. The role of DAB2IP in pancreatic cancer was further investigated in vitro and in vivo by upregulating DAB2IP in Bxpc-3 cells through transfection of DAB2IP into Bxpc-3 cells with recombinant lentivirus. The DAB2IP expression in pancreatic cancer cells and tissues with wild-type KRAS was significantly lower than that in cells and tissues with mutant KRAS ( P < .05). In Bxpc-3 cells with wild-type KRAS, overexpression of DAB2IP decreased the expression of P-AKT and P-ERK and the Ras activity; increased the expression of P-JNK and caspase 3; inhibited cell proliferation, invasiveness, and migration; and increased the cell sensitivity to cetuximab. Overexpression of DAB2IP inhibited tumor progression in a mouse model. In conclusion, DAB2IP downregulates Ras activity in wild-type pancreatic cancer cells. Overexpression of DAB2IP decreases the Ras activity, inhibits cell proliferation, and increases sensitivity to cetuximab in wild-type pancreatic cancer cells. In conclusion, DAB2IP may serve as a potential molecular therapeutic target for the treatment of pancreatic cancer.

Esophageal carcinoma, with a increasing incidence, is one of the most aggressive carcinomas in gastrointestinal tract. Epidemiologic studies demonstrate an association of oral pathogens with multiple diseases, including rheumatoid arthritis, cardiovascular diseases, diabetes, and gastrointestinal malignancies. Nevertheless, a causal relationship between oral pathogens and esophageal squamous cell carcinoma (ESCC) has not been elucidated. Here, we found that Porphyromonas was significantly enriched in the saliva of patients with ESCC, compared with that in normal human. In vitro studies showed that Porphyromonas gingivalis (P. gingivalis) promoted the proliferation and motility of ESCC cells, as evidenced by up regulated expression of key molecules implicated in NF-κB signaling pathway. These findings, for the first time, demonstrated a role of oral pathogens in inducing ESCC tumorigenesis and metastasis, which might involve regulation of NF-κB signaling pathway.

As the rapid growth of wireless traffic demands, the current wireless technology will be bounded in the next 10 years. To struggle for the high network capacity demands provoked by the explosion of current services, significant improvement to wireless access techniques have been made. Thus, it becomes complicated to design future 5G communication infrastructures while taking advantage of novel spectrum/radio technologies. Currently, mobile operators have been deploying heterogeneous networks to boost network capacity and coverage. Furthermore, in order to achieve better spectral efficiency, potential technologies for reconfigurable networks have been investigated, such as software-defined radio (SDR), cognitive radio (CR), and cognitive networks (CNs). However, those new characteristics, as well as novel spectral efficiency technologies for 5G, need to be further studied. In particular, how to apply spectral efficiency technologies on the newly developed network architectures should be actively addressed and discussed.

Urban rail transit systems are being extended throughout the world because of their large capacities, avoidance of traffic congestion, and environmental advantages. Various optimization models can help design rail transit alignments satisfying various track geometry constraints, but none of these models can account for the impacts of vehicle dynamics on operational and user costs. This paper presents a practical rail transit alignment optimization method for designing track alignments that accounts for vehicle dynamics. The method can generate alignments that improve the balance between the initial cost and the operation and user costs recurring throughout the system's life cycle. A heuristic based on a genetic algorithm is developed to search for solutions efficiently while interacting with the supporting geographic information system. A hypothetical topography scenario is created to illustrate the impact of vehicle dynamics on the trade-offs among system costs. The Baltimore, Maryland, Red Line is used as a case study to demonstrate that the model can find good solutions in regions with complex topographies.

To meet the requirements of 5G on enabling higher capacity, faster rates, more connectivity, higher reliability, lower latency, greater versatility, and application-domain specific topologies, new concepts and design approaches are in great need. Current standards for 4G may influence the introduction of radio features and network solutions for 5G systems. New network architectures extending beyond heterogeneous networks and exploiting new frequency spectra (e.g., millimeter wave) are emerging from research laboratories around the world. In addition to the network side, advanced terminals and receivers are being developed to optimize network performances. Splitting the control and data planes [currently studied in 3G Partnership Project (3GPP)] is an interesting paradigm for 5G, together with massive multi-input multi-output (MIMO), advanced antenna systems, software-defined networking (SDN), network functions virtualization (NFV), the Internet of Things, and cloud computing. Also, new radio protocols enabling heterogeneous traffics are required.

The evacuation of large municipal areas in an efficient manner during emergencies and disasters is one of the critical tasks of emergency management agencies. This paper presents a corridor-based emergency evacuation system and an example application of the system for the Washington, D.C., metropolitan area. The proposed system features flexibility by accounting for various critical issues associated with both planning and real-time operations, including the integration of data from multiple sources, network decomposition, network-level traffic routing, contraflow design, staged evacuation, optimal signal timing, and the incorporation of pedestrian and bus operations. Under a hypothetical emergency scenario for Union Station in Washington, D.C., the proposed system demonstrated its effectiveness at producing evacuation routing strategies, identifying potential bottlenecks, and evaluating the performance of evacuation operations.

This paper presents a two-level integrated optimization system for use in generating the candidate set of optimal evacuation plans that serve as the input for simulation-based evacuation systems. In the proposed system, the high-level optimization aims to maximize the throughput during the specified evacuation duration, and the low-level optimization is intended to minimize the total travel time as well as the waiting time for the entire operation if the specified duration is sufficient for meeting all evacuation demands. To effectively represent traffic flow relations with mathematical formulations, this paper employs the cell transmission concept, but with a revised formulation for large-scale network applications. The performance of the proposed models and their applicability has been tested with a microscopic simulation program that replicates the Ocean City evacuation network. Evaluation results from these numerical studies have demonstrated the promising properties of the proposed integrated optimization system.

Staged evacuation is widely used in emergency situations in which different parts of the target network may suffer different levels of severity over different time windows. By evacuating those populations in the network via an optimized sequence, the staged evacuation strategy can best use available roadway capacity, optimally distribute the total demand over the evacuation time horizon, and thus minimize the network congestion level. This study proposes a cell-based network model to capture critical characteristics associated with staged evacuation operations. The proposed model shows the ability to reflect incident impacts and arrival patterns of evacuees in computing the optimal starting time and routes for each evacuation zone. Preliminary numerical results have demonstrated the potential for applying the proposed staged evacuation model in real-world emergency management and planning.

The framework and field application of a simulation-based online system for travel time prediction are presented. The proposed system is designed to contend with most critical issues associated with real-time operations, which include estimation of missing volumes, detection of incidents, data filtering, and computation of traffic volumes for projected time intervals so as to activate the simulation function. The proposed system was deployed on two routes of 30 mi between Salisbury and Ocean City, Maryland, with a total of 10 detectors. The preliminary application results clearly indicate that with proper integration the proposed system offers a cost-effective tool for real-time travel time prediction.

This paper presents a mixed-integer model for design of arterial signal control strategies during emergency evacuation. The proposed model can effectively take into account various complex operational issues such as critical intersection selection, demand rerouting, and signal timing. The control objective is to maximize the efficiency of the primary evacuation arterial, but not incur excessive waiting time and queues on its side streets. To evaluate the effectiveness of the proposed model under various demand levels and control objectives, this study has employed one major evacuation corridor in Washington D.C. as the target route for numerical experiments. The results of extensive simulation experiments reveal that the proposed method for signal optimization offers the potential for real-world applications.

Complicated Electronic Medical Records (EMR) systems have created problems in systems regarding an easy implementation and interoperability for a Web-enabled Healthcare Solution, which is normally provided by an independent healthcare giver with limited IT knowledge and interests. An EMR system with well-designed and user-friendly interface, such as Microsoft HealthVault System used as the back-end platform of a Web-enabled healthcare application will be an approach to deal with these problems. This paper analyzes the patient oriented Web-enabled healthcare service application as the new trend to delivery healthcare from hospital/clinic-centric to patient-centric, the current e-healthcare applications, and the main backend EMR systems. Then, we present a novel web-enabled healthcare solution based on Microsoft HealthVault EMR system to meet customers' needs, such as, low total cost, easily development and maintenance, and good interoperability. A sample system is given to show how the solution can be fulfilled, evaluated, and validated. We expect that this paper will provide a deep understanding of the available EMR systems, leading to insights for new solutions and approaches driven to next generation EMR systems.

This paper has investigated critical issues associated with Optimal Detector Locations for OD matrix estimation, including a discussion of limitations embedded in existing models and algorithms. A heuristic algorithm has been proposed for identifying the optimal set of detector locations under a given budget constraint for effective OD matrix estimation. The numerical experiment results have indicated that the proposed algorithm is quite promising for potential applications.

As the swift development and deployment of WiFi networking infrastructure with the lower price to provide the wider coverage, WiFi-based positioning approaches have been one of the 'best practices' in both outdoor and indoor environment. In this paper, an overview of various approaches for WiFi-based positioning is presented. The WiFi-based positioning approaches are categorised into cell-ID, angle of arrival (AOA), received signal strength (RSS), time of arrival (TOA) and time difference of arrival (TDOA). The basic idea and ranging accuracy are presented to compare the different approaches. As the most practical methods, fingerprinting and TDOA approaches are elaborated and some advanced methods based on them are also provided to show the improvement. The different approaches are basically evaluated by their ranging accuracy, but the system privacy and scalability, as the other two key directions to evaluate a positioning system, are also discussed in this paper.