Pervasive 2007: It's about the User

Pervasive computing is as much about the user as it is about the technology. So, the Fifth International Conference on Pervasive Computing emphasized desirability rather than just feasibility. Featured themes included user benefits, human-computer interaction, group and social interactions, context awareness, finding and positioning people and objects, and personal privacy.     

Partitioning multiple objective optimal solutions with applications in radiotherapy design

The optimal partition for linear programming is induced by any strictly complementary solution, and this partition is important because it characterizes the optimal set. However, constructing a strictly complementary solution in the presence of degeneracy was not practical until interior point algorithms became viable alternatives to the simplex algorithm. We develop analogs of the optimal partition for linear programming in the case of multiple objectives and show that these new partitions provide insight into the optimal set (both pareto optimality and lexicographic ordering are considered). Techniques to produce these optimal partitions are provided, and examples from the design of radiotherapy plans show that these new partitions are useful. A. Holder. Research conducted at Trinity University, TX, and The University of Mississippi, MS. This research was partially supported by ONR Grant N00014-01-1-0917.     

Segmental reflex sympathetic dystrophy: clinical and scintigraphic criteria

Clinical and scintigraphic criteria are proposed for the diagnosis of segmental reflex sympathetic dystrophy. Eight patients met previously described clinical criteria for reflex sympathetic dystrophy with involvement limited to only a portion of the hand. The delayed phase of the three-phase radionuclide bone scan was found to be highly sensitive (100%) for this small group of patients. Consecutive bone scans (n = 127) performed during a 6-month period for a variety of upper extremity problems were reviewed, and a segmentally diffuse pattern of tracer uptake was found to be highly specific (98%) for segmental reflex sympathetic dystrophy. Recognition and documentation of a more localized form of reflex sympathetic dystrophy will allow earlier recognition and treatment, which is an important factor in a successful outcome for managing pain dysfunction disorders.     

Development of technologies aiding large-tissue engineering

Apoptosis associated oligonucleosomal fragmentation of DNA can result from the activation of endonucleases that exhibit different pH optima and are either sensitive or insensitive to divalent cations. DNA fragmentation due to activation of cation sensitive endonucleases occurs in the absence of a change in intracellular pH whereas intracellular acidification is a feature of apoptosis characterized by activation of cation insensitive acidic endonuclease. We have reported earlier that somatostatin (SST) induced DNA fragmentation and apoptosis is signaled in a receptor subtype selective manner uniquely via human somatostatin receptor subtype 3 (hSSTR3). In the present study we investigated the pH dependence and cation sensitivity of endonuclease induced in hSSTR3 expressing CHO-K1 cells by the SST agonist octreotide (OCT) and its effect on intracellular pH. We show that OCT induced apoptosis is associated with selective stimulation of a divalent cation insensitive acidic endonuclease. The intracellular pH of of cells undergoing OCT induced apoptosis was 0.9 pH units lower than that of control cells. The effect of OCT on endonuclease and pH was inhibited by orthovanadate as well as by pretreatment with pertussis toxin, suggesting that hSSTR3 initiated cytotoxic signaling is protein tyrosine phosphatase mediated and is G protein dependent. These findings suggest that intracellular acidification and activation of acidic endonuclease mediate wild type p53 associated apoptosis signaled by hormones acting via G protein coupled receptors.     

The Impact of Fluid Dynamic Stress in Stirred Bioreactors – The Scale of the Biological Entity: A Personal View

From the start of industrial biotechnology, there has been a perception that biological entities are damaged by stirring, so-called ‘shear damage'. Often, it was the soft option to explain a loss of performance when it was due to other factors, such as bubble ingestion with proteins or on scale-up, where tip speed increased when it was due to decreased homogeneity, especially in pH. For many years, poor control and the range of analytical tools available made a more in-depth explanation difficult; and the concepts of ‘high' and ‘low shear' impellers, now largely disproven, increased it. Here, the size of the biological entity is compared to the Kolmogorov microscale of turbulence leading to a reasonably clear picture emerging. The article starts with the author's introduction to the issue approximately 42 year ago with enzymes, conveniently also the smallest entity; and finishes with the largest, filamentous fungi.     

确保管道运输的泄漏检测技术

保证所有管道中石油从一端流向另一端不泄漏要比它的探测更加困难。比较图中的3个系统,可以看到这项技术在40多年来是如何逐步发展的。     

The Role of Deep Learning in Parking Space Identification andPredictionSystems

In today’s smart city transportation, traffic congestion is a vexing issue, and vehicles seeking parking spaces have been identified as one of the causes leading to approximately 40% of traffic congestion. Identifying parking spaces alone is insufficient because an identified available parking space may have been taken by another vehicle when it arrives, resulting in the driver’s frustration and aggravating traffic jams while searching for another parking space. This explains the need to predict the availability of parking spaces. Recently, deep learning (DL) has been shown to facilitate drivers to find parking spaces efficiently, leading to a promising performance enhancement in parking identification and prediction systems. However, no work reviews DL approaches applied to solve parking identification and prediction problems. Inspired by this gap, the purpose of this work is to investigate, highlight, and report on recent advances in DL approaches applied to predict and identify the availability of parking spaces. A taxonomy of DL-based parking identification and prediction systems is established as a methodology by classifying and categorizing existing literature, and by doing so, the salient and supportive features of different DL techniques for providing parking solutions are presented. Moreover, several open research challenges are outlined. This work identifies that there are various DL architectures, datasets, and performance measures used to address parking identification and prediction problems. Moreover, there are some open-source implementations available that can be used directly either to extend existing works or explore a new domain. This is the first short survey article that focuses on the use of DL-based techniques in parking identification and prediction systems for smart cities. This study concludes that although the deployment of DL in parking identification and prediction systems provides various benefits, the convergence of these two types of systems and DL brings about new issues that must be resolved in the near future.