Miracle-dz/UniFAR-FTUs huggingface dataset:
Ex Vivo Expanded Human Regulatory T Cells Delay Islet Allograft Rejection via Inhibiting Islet-Derived Monocyte Chemoattractant Protein-1 Production in CD34+ Stem Cells-Reconstituted NOD-scid IL2rγnull Mice

Type 1 diabetes mellitus (T1DM) is an autoimmune disease caused by immune-mediated destruction of insulin-secreting β cells of the pancreas. Near complete dependence on exogenous insulin makes T1DM very difficult to control, with the result that patients are exposed to high blood glucose and risk of diabetic complications and/or intermittent low blood glucose that can cause unconsciousness, fits and even death. Allograft transplantation of pancreatic islets restores normoglycemia with a low risk of surgical complications. However, although successful immediately after transplantation, islets are progressively lost, with most of the patients requiring exogenous insulin within 2 years post-transplant. Therefore, there is an urgent requirement for the development of new strategies to prevent islet rejection. In this study, we explored the importance of human regulatory T cells in the control of islets allograft rejection. We developed a pre-clinical model of human islet transplantation by reconstituting NOD-scid IL2rγnull mice with cord blood-derived human CD34+ stem cells and demonstrated that although the engrafted human immune system mediated the rejection of human islets, their survival was significantly prolonged following adoptive transfer of ex vivo expanded human Tregs. Mechanistically, Tregs inhibited the infiltration of innate immune cells and CD4+ T cells into the graft by down-regulating the islet graft-derived monocyte chemoattractant protein-1. Our findings might contribute to the development of clinical strategies for Treg therapy to control human islet rejection. We also show for the first time that CD34+ cells-reconstituted NOD-scid IL2rγnull mouse model could be beneficial for investigating human innate immunity in vivo.
MobiCom 2010 Poster : Exploiting Routing Redundancy using MAC layer Anycast to Improve Delay in WSN

Source-destination pairs in wireless sensor networks often have multiple shortest hop paths because the nodes are densely deployed. These multiple paths provide a great opportunity to reduce delay in an asynchronous duty-cycled network. In this paper, we exploit the redundancy available at the route layer using MAC-layer anycasting. We choose the next hop node that wakes up the soonest and thus reduce the delay incurred at each hop.
Management and organizational topics in virtual enterprises – business drivers , characteristics and issues in collaborative environments

A large number of research initiatives and industry cases focusing on virtual enterprises (VE) or enterprise networks have been developed world-wide during the last years. This paper presents a synopsis of results from various research projects. Although the use of appropriate information and communication technology (ICT) is a prerequisite for and a critical element in efficient collaborations, human factors, organizational and management issues are still under development and further research on business drivers and success factors of virtual enterprises is required. Key-Words: Virtual enterprise, source networks, management concepts, collaborative business.
Title: Size and Shape Variability in Human Molars during Odontogenesis 2 3

4 Under the patterning cascade model (PCM) of cusp development inspired by developmental 5 genetic studies, it is predicted that the location and the size of later-forming cusps are more variable than 6 those of earlier-forming ones. Here we assessed whether differences in the variability among cusps at 7 total and each particular crown components (enamel-dentin junction [EDJ], outer enamel surface [OES], 8 and cement-enamel junction [CEJ]) could be explained by the PCM, using human maxillary permanent 9 first molars (UM1) and second deciduous molars (um2). Specimens were μCT-scanned, and 3D models 10 of EDJ and OES were reconstructed. Based on these models, landmark-based 3D geometric 11 morphometric analyses were conducted. Size variability in both tooth types was generally consistent 12 with the above prediction, and the differences in size variation among cusps were smaller for the crown 13 components that are completed in later stages of odontogenesis. With a few exceptions, however, the 14 prediction was unsupported regarding shape variability, and UM1 and um2 showed different patterns. 15 Our findings suggested that the pattern of size variability would be caused by temporal factors such as 16 the order of cusp initiation and the duration from the beginning of mineralization to the completion of 17 crown formation, whereas shape variability may be affected by both topographic and temporal factors.
Information Technology and Corporate Strategy: A Research Perspective

The use of information technology (IT) as a competitive weapon has become a popular cliche; but there is still a marked lack of understanding of the issues that determine the influence of information technology on a particular organization and the processes that will allow a smooth coordination of technology and corporate strategy. This article surveys the major efforts to arrive at a relevant framework and attempts to integrate them in a more comprehensive viewpoint. The focus then turns to the major research issues in understanding the impact of information technology on competitive strategy.
Light, temperature and competition : understanding the causes for climate-driven regime shifts in arctic marine benthos

In the Arctic, shallow sea-floor communities have been documented to shift abruptly from an invertebrate-dominated state to a state with high macroalgal abundance. Climate warming, resulting in increased water temperatures and decreased sea ice cover, could trigger such regime shifts in benthic ecosystems, but the underlying mechanisms are not clear. To gain a better understanding, a mechanistic model of algal growth and interspecific competition was applied in two marine ecosystems in northwestern Svalbard. Unravelling the effects of light and temperature on the model parameters, the current study showed that light is a key factor determining the algal dominance in the two ecosystems. Changes in sea-ice cover, which alters the underwater light regime, is therefore considered the most likely trigger for invertebratealgae regime shifts. A continued prolonging of the ice-free season in the Arctic is likely to occur in the upcoming years, considering the current climatic development. Thus, it is expected that macroalgal cover in shallow rocky-bottom communities will continue to increase, altering species composition and function in seasonally ice-covered arctic ecosystems.
An improved branch and bound algorithm for the maximum clique problem

A new algorithm for finding a maximum clique in an undirected graph is described. An approximate coloring algorithm has been improved and used to provide bounds to the size of the maximum clique in a basic algorithm which finds a maximum clique. This basic algorithm was then extended to include dynamically varying bounds. The resulting algorithm is significantly faster than the comparable algorithm.
Fast algorithm on parameter estimation of wideband LFM signal based on down-chirp and CS

Compressed Sensing (CS) has been successfully applied to the parameter estimation of Linear Frequency Modulation (LFM) signal. Compared to the Nyquist sampling method, far less samples are needed to estimate the frequency parameter. However, the super-resolution estimation of frequency parameter can greatly increase the number of atoms in the over-complete dictionary and it will brings a huge amount of computation. This paper proposes resolutions to this problem. Taking the feature of CS into account that the sampling and compression are completed at the same time, we structure a measurement matrix which can complete the compressive sampling and down-chirp simultaneously. Furthermore, we propose a down-chirp based method and improve it with fast computing strategy to solve the above problem. Simulation results have proved that the frequency parameter can be accurate estimated under a low SNR and sampling condition. Meanwhile, compared with the proposed method, the improved algorithm greatly reduces the scale of over-complete dictionary and the amount of computation, and the estimation time has been cut down significantly.
Distributed Application-layer Rate Control for Efficient Multipath Data Transfer via TCP

For applications involving data transmission from multiple sources, an important problem is: when the sources use multiple paths, how to maximize the aggregate sending rate of the sources using application-layer techniques via TCP? We develop an application-level distributed rate controller to solve this problem. Our controller utilizes the bandwidth probing mechanisms embedded in TCP and does not require explicit network knowledge (e.g., topology, available bandwidth). We theoretically prove the convergence of our algorithm in certain settings. Furthermore, using a combination of simulation and testbed experiments, we demonstrate that our algorithm provides efficient multipath data transfer and is easy to deploy.
An Integration of ANN Wind Power Estimation Into Unit Commitment Considering the Forecasting Uncertainty

The development of wind power generation has rapidly progressed over the last decade. With the advancement in wind turbine technology, wind energy has become competitive with other fuel-based resources. The fluctuation of wind, however, makes it difficult to optimize the usage of wind power. The current practice ignores wind generation capacity in the unit commitment (UC), which discounts its usable capacity and may cause operational issues when the installation of wind generation equipment increases. To ensure system reliability, the forecasting uncertainty must be considered in the incorporation of wind power capacity into generation planning. This paper discusses the development of an artificial-neural-network-based wind power forecaster and the integration of wind forecast results into UC scheduling considering forecasting uncertainty by the probabilistic concept of confidence interval. The data from a wind farm located in Lawton City, OK, is used in this paper.
Repeated Schistosoma japonicum Infection Following Treatment in Two Cohorts: Evidence for Host Susceptibility to Helminthiasis?

Background In light of multinational efforts to reduce helminthiasis, we evaluated whether there exist high-risk subpopulations for helminth infection. Such individuals are not only at risk of morbidity, but may be important parasite reservoirs and appropriate targets for disease control interventions. Methods/Principal Findings We followed two longitudinal cohorts in Sichuan, China to determine whether there exist persistent human reservoirs for the water-borne helminth, Schistosoma japonicum, in areas where treatment is ongoing. Participants were tested for S. japonicum infection at enrollment and two follow-up points. All infections were promptly treated with praziquantel. We estimated the ratio of the observed to expected proportion of the population with two consecutive infections at follow-up. The expected proportion was estimated using a prevalence-based model and, as highly exposed individuals may be most likely to be repeatedly infected, a second model that accounted for exposure using a data adaptive, machine learning algorithm. Using the prevalence-based model, there were 1.5 and 5.8 times more individuals with two consecutive infections than expected in cohorts 1 and 2, respectively (p<0.001 in both cohorts). When we accounted for exposure, the ratio was 1.3 (p = 0.013) and 2.1 (p<0.001) in cohorts 1 and 2, respectively. Conclusions/Significance We found clustering of infections within a limited number of hosts that was not fully explained by host exposure. This suggests some hosts may be particularly susceptible to S. japonicum infection, or that uncured infections persist despite treatment. We propose an explanatory model that suggests that as cercarial exposure declines, so too does the size of the vulnerable subpopulation. In low-prevalence settings, interventions targeting individuals with a history of S. japonicum infection may efficiently advance disease control efforts.
Estudi dels canvis morfològics en el pols cardíac associats a la respiració i postura

On the last decades, there has been many discoveries regarding the analysis on the heart rhythm and heart rate variability. Influences have been found due to age, exercise, gender and other factors. The objective of this thesis in particular is to make a study where we will measure the heart rhythm of a group of volunteers in different postures and breath rhythm. In order to achieve this objective, four different points representing the heart pulse signal morphology will be extracted. Using the signals obtained from those four points, an analysis on the differences will be made in order to look for influences due to breath rhythm or posture. The methodology, work plan and other factors which influenced in the project's development will also be explained. Finally, conclusions about the relation in the influence of posture and breath rhythm in the heart pulse signal morphology will be obtained.
Comparative study between different classifiers based speaker recognition system using MFCC for noisy environment

Speaker recognition has made great progress under the laboratory environment, but in real life the performance of speaker recognition system is affected by various factors including environmental noise. This paper studies the performance of speaker recognition system in noisy environment and presents Speaker recognition system using Mel-Frequency Cepstral Coefficients (MFCC) technique based on different classifiers likes Euclidean distance, Back-Propagation Neural Network (BPNN), Self Organizing Map (SOM). This paper presents comparative plots of different classifier. Speaker recognition system based on SOM Neural Network classifier is provide better recognition rate compare to BPNN and Euclidean Distance based systems.
Managing Heterogeneity in Structured Peer-to-Peer Systems

WANG, CHIH-CHIANG. Managing Heterogeneity in Structured Peer-to-Peer Systems. (Under the direction of Assistant Professor Khaled Harfoush). Peer-to-Peer (P2P) systems account for more than 60% of today’s Internet traffic. P2P success is attributed to the virtually unlimited capacity offered by its members, the resilience to failures, and features such as anonymous service. P2P systems are inherently heterogeneous. Members may have different service capacities, different Internet connectivity speeds, and spend different times in the system. Heterogeneity impacts the scalability of P2P systems, its ability to serve user requests and the perceived user performance. P2P systems need to be engineered to accommodate node heterogeneity. In this dissertation, we present two studies on node heterogeneity in structured P2P systems. In the first study, we analyze routing performance in the presence of P2P overlay irregularity caused by the heterogeneous capacity of peers. We pinpoint how Greedy routing deviates from shortest path routes and propose a novel routing protocol, RASTER, which uncovers shortest routes in irregular overlays. In the second study, we provide an analytical model that captures the tradeoff between the stability and the scalability in P2P systems. We use the model to demonstrate that P2P instability can be mitigated and system throughput can be optimized through careful selection of serving members and data redundancy parameters. Our model reveals appropriate trends in engineering P2P systems under bandwidth and storage constraints, the skew in the size and popularity of maintained content, and the workload imposed on the system. We highlight the performance limitations of P2P systems as expressed in terms of the system throughput and response time to user requests in the presence of node instability. Our results challenge common wisdom about P2P systems, their appropriateness for different applications, and their virtually unlimited capacity. Managing Heterogeneity in Structured Peer-to-Peer Systems
Probabilistic representation of gene regulatory networks

MOTIVATION Recent experiments have established unambiguously that biological systems can have significant cell-to-cell variations in gene expression levels even in isogenic populations. Computational approaches to studying gene expression in cellular systems should capture such biological variations for a more realistic representation. RESULTS In this paper, we present a new fully probabilistic approach to the modeling of gene regulatory networks that allows for fluctuations in the gene expression levels. The new algorithm uses a very simple representation for the genes, and accounts for the repression or induction of the genes and for the biological variations among isogenic populations simultaneously. Because of its simplicity, introduced algorithm is a very promising approach to model large-scale gene regulatory networks. We have tested the new algorithm on the synthetic gene network library bioengineered recently. The good agreement between the computed and the experimental results for this library of networks, and additional tests, demonstrate that the new algorithm is robust and very successful in explaining the experimental data. AVAILABILITY The simulation software is available upon request. SUPPLEMENTARY INFORMATION Supplementary material will be made available on the OUP server.
Flatness-Based Trajectory Planning/Replanning for a Quadrotor Unmanned Aerial Vehicle

A flatness-based flight trajectory planning/replanning strategy is proposed for a quadrotor unmanned aerial vehicle (UAV). In the nominal situation (fault-free case), the objective is to drive the system from an initial position to a final one without hitting the actuator constraints while minimizing the total time of the mission or minimizing the total energy spent. When actuator faults occur, fault-tolerant control (FTC) is combined with trajectory replanning to change the reference trajectory in function of the remaining resources in the system. The approach employs differential flatness to express the control inputs to be applied in the function of the desired trajectories and formulates the trajectory planning/replanning problem as a constrained optimization problem.
Distinct Neural Activity Associated with Focused-Attention Meditation and Loving-Kindness Meditation

This study examined the dissociable neural effects of ānāpānasati (focused-attention meditation, FAM) and mettā (loving-kindness meditation, LKM) on BOLD signals during cognitive (continuous performance test, CPT) and affective (emotion-processing task, EPT, in which participants viewed affective pictures) processing. Twenty-two male Chinese expert meditators (11 FAM experts, 11 LKM experts) and 22 male Chinese novice meditators (11 FAM novices, 11 LKM novices) had their brain activity monitored by a 3T MRI scanner while performing the cognitive and affective tasks in both meditation and baseline states. We examined the interaction between state (meditation vs. baseline) and expertise (expert vs. novice) separately during LKM and FAM, using a conjunction approach to reveal common regions sensitive to the expert meditative state. Additionally, exclusive masking techniques revealed distinct interactions between state and group during LKM and FAM. Specifically, we demonstrated that the practice of FAM was associated with expertise-related behavioral improvements and neural activation differences in attention task performance. However, the effect of state LKM meditation did not carry over to attention task performance. On the other hand, both FAM and LKM practice appeared to affect the neural responses to affective pictures. For viewing sad faces, the regions activated for FAM practitioners were consistent with attention-related processing; whereas responses of LKM experts to sad pictures were more in line with differentiating emotional contagion from compassion/emotional regulation processes. Our findings provide the first report of distinct neural activity associated with forms of meditation during sustained attention and emotion processing.
Title Regulating the Effects of Depletion through Monitoring Rights Creative Commons: Attribution 3.0 Hong Kong License Regulating Depletion Effects 1 Regulating the Effects of Depletion through Monitoring

A robust finding is that participants who perform a depleting initial self-regulatory task are less persistent on a contiguous second task than those who perform a less arduous initial selfregulatory task. We explain this regulatory depletion effect in terms of a monitoring process. According to this view, depleted individuals focus on the resources they have devoted to a second task, neglect to monitor their performance against their standards for such activities, and prematurely suspend their performance. Consistent with this view, we demonstrate that the regulatory depletion effect can be eliminated when individuals are encouraged to monitor their performance against some standard (Studies 1, 2 and 4), or when they have a proclivity to engage in such monitoring (Studies 3 and 4).
Some memoryless bandit policies

We consider a multiarmed bandit problem, where each arm when pulled generates independent and identically distributed nonnegative rewards according to some unknown distribution. The goal is to maximize the long-run average reward per pull with the restriction that any previously learned information is forgotten whenever a switch between arms is made. We present several policies and a peculiarity surrounding them.
Apps-usage driven energy management for multicore mobile computing systems

This paper presents an idea to redesign the existing mobile computing system scheduler with Apps-usage awareness. By identifying the Apps-usage patterns, we model the relationship between system power consumption and different combinations of Apps. As observed some of the Apps combinations produce more power dissipation comparing to the others. The proposed scheduler reorders the Apps scheduling sequence according to the recorded Apps combination and power consumption values, hence minimizing the overall power consumption. The scheduling schemes are tested in a simulated environment built with GEM5 and McPat. The simulated result shows power consumption reduction up to 19%.