Counting anticoincidences to reduce statistical uncertainty in the calibration of a multiplicity detector

The observation of anticoincidences reduced statistical uncertainties as well as pileup corrections in the efficiency calibration of a multiplicity detector. The efficiency of the 4π gadolinium-loaded organic scintillation detector was measured for detecting capture of neutrons scattered by the hydrogen in a second detector. In such situations the effect of background upon the counting fluctuations is reduced below the value that would occur if the average counting rate during coincidence gates were utilized. The applicable formulae were obtained by elementary methods and were verified with experimental data and with computer simulations for a broad range of detector efficiencies and background intensities. The general requirements for use of the technique are indicated.     

Synapses: The Brain’s Energy-Demanding Sites

The brain is one of the most energy-consuming organs in the mammalian body, and synaptic transmission is one of the major contributors. To meet these energetic requirements, the brain primarily uses glucose, which can be metabolized through glycolysis and/or mitochondrial oxidative phosphorylation. The relevance of these two energy production pathways in fulfilling energy at presynaptic terminals has been the subject of recent studies. In this review, we dissect the balance of glycolysis and oxidative phosphorylation to meet synaptic energy demands in both resting and stimulation conditions. Besides ATP output needs, mitochondria at synapse are also important for calcium buffering and regulation of reactive oxygen species. These two mitochondrial-associated pathways, once hampered, impact negatively on neuronal homeostasis and synaptic activity. Therefore, as mitochondria assume a critical role in synaptic homeostasis, it is becoming evident that the synaptic mitochondria population possesses a distinct functional fingerprint compared to other brain mitochondria. Ultimately, dysregulation of synaptic bioenergetics through glycolytic and mitochondrial dysfunctions is increasingly implicated in neurodegenerative disorders, as one of the first hallmarks in several of these diseases are synaptic energy deficits, followed by synapse degeneration.     

Microfluidic-Based Cationic Cholesterol Lipid siRNA Delivery Nanosystem: Highly Efficient In Vitro Gene Silencing and the Intracellular Behavior

Safe and efficient delivery of small interfering RNA (siRNA) is essential to gene therapy towards intervention of genetic diseases. Herein, we developed a novel cationic cholesterol lipid derivative (CEL) in which cholesterol hydrophobic skeleton was connected to L-lysine cationic headgroup via a hexanediol linker as the non-viral siRNA delivery carrier. Well-organized CEL/siRNA nanocomplexes (100–200 nm) were prepared by microfluidic-assisted assembly of CEL and siRNA at various N/P ratios. The CEL and CEL/siRNA nanocomplexes have lower cytotoxicity compared with bPEI25k. Delightfully, we disclosed that, in Hela–Luc and H1299–Luc cell lines, the micro-fluidic-based CEL/siRNA nanocomplexes exhibited high siRNA transfection efficiency under both serum-free condition (74–98%) and low-serum circumstances (80–87%), higher than that of lipofectamine 2000. These nanocomplexes also showed high cellular uptake through the caveolae/lipid-raft mediated endocytosis pathway, which may greatly contribute to transfection efficiency. Moreover, the time-dependent (0–12 h) dynamic intracellular imaging demonstrated the efficient delivery to cytoplasm after lysosomal co-localization. The results indicated that the microfluidic-based CEL/siRNA nanosystems possessed good stability, low cytotoxicity, high siRNA delivery efficiency, rapid cellular uptake and caveolae/lipid raft-dependent internalization. Additionally, this study provides a simple approach for preparing and applying a “helper lipid-free” cationic lipid siRNA delivery system as potential nanotherapeutics towards gene silencing treatment of (tumor) diseases.     

The minisum location problem on an undirected network with continuous link demands

In the one-median problem, a facility is to be located on a network minimizing total travel distances from the facility to customer demands restricted to nodal locations. In reality, however, demands do occur on links of a network. Thus, aggregation of or restriction to nodal demands may not be a satisfactory approximation. In this paper, we generalize the one-median problem to a network with discrete nodal as well as general continuous link demands. Properties of the total travel distance, as a function of the facility's location, are examined. We introduce an exact and a heuristic procedure to find an optimal location for the facility. An efficient algorithm is developed when the network is a tree.     

Hyperthermia Enhances Doxorubicin Therapeutic Efficacy against A375 and MNT-1 Melanoma Cells

Melanoma is the deadliest form of skin cancer, and its incidence has alarmingly increased in the last few decades, creating a need for novel treatment approaches. Thus, we evaluated the combinatorial effect of doxorubicin (DOX) and hyperthermia on A375 and MNT-1 human melanoma cell lines. Cells were treated with DOX for 24, 48, and 72 h and their viabilities were assessed. The effect of DOX IC10 and IC20 (combined at 43 °C for 30, 60, and 120 min) on cell viability was further analyzed. Interference on cell cycle dynamics, reactive oxygen species (ROS) production, and apoptosis upon treatment (with 30 min at 43 °C and DOX at the IC20 for 48 h) were analyzed by flow cytometry. Combined treatment significantly decreased cell viability, but not in all tested conditions, suggesting that the effect depends on the drug concentration and heat treatment duration. Combined treatment also mediated a G2/M phase arrest in both cell lines, as well as increasing ROS levels. Additionally, it induced early apoptosis in MNT-1 cells, while in A375 cells this effect was similar to the one caused by hyperthermia alone. These findings demonstrate that hyperthermia enhances DOX effect through cell cycle arrest, oxidative stress, and apoptotic cell death.     

The classification of defects from ultrasonic data using neural networks: The Hopfield method

Neural network algorithms offer a method of classification of multi-parameter data which is both rapid and tolerant of noisy data. Here the Hopfield model is used to classify processed ultrasonic data from various known classes of defect within steel test welds. Some 83 defects, from four known categories, and described by up to six feature parameters, were used in the analysis. A randomly chosen fraction of the set was used to produce images characteristic of each defect class. These were memorized into the network. Defects in the remaining fraction of the dataset were then recalled by the network, together with statistical information on the degree of confidence of the identification. An accuracy of 100% was often achieved when 50% fractions of the data were used for training and for testing. The accuracy achieved is comparable with that given by conventional minimum distance classification algorithms.     

Intelligent gateway troubleshooter

The Intelligent Gateway Troubleshooter (IGT) is an expert system that has captured some of the network management knowledge of network operators and analysts. Specifically, it involves the detection and diagnosis of problems in the DARPA internet. One important feature of the system is that it works in real time. That is, the detection and diagnosis of relevant events are alerted to a user of the system as they occur. Another feature of the system is that it provides a means of integrating expertise from several domains. This is important because network management expertise is spread amongst several types of human domain experts.The domain of IGT assumes that any anomaly is caused by only one fault. For example, if a gateway does not respond, then the system never attributes this to two different problems. This does not mean, however, that the system does not consider multiple faults. Nonetheless, for the system to consider multiple faults, there must be multiple anomalies.     

Optical processing of banded matrix algorithms using outer product concepts

Optical processing devices, whose designs are based on systolic and other array processor architectures, have been developed for performing a variety of signal and image processing tasks.In this paper a Modified Outer Product Processor is proposed for the implementation of banded matrix algorithms, i.e. triangularization of a matrix, direct solution of linear systems of equations and matrix inversion; all based on the Gaussian elimination algorithm.The modified optical processor requires less and simpler hardware, it is size-independent, requires no preloading of the full matrix but it works with the ‘active window’ of the matrix, defined as the elements that are currently being involved in the computation.     

Chebyshev economization for parametric surfaces

The communication of polynomial curve and surface data between various CAD systems frequently requires that a degree reduction be performed. The most common way of accomplishing this reduction at present is via ‘black box’ methods. In this note we extend the notion of Chebyshev economization from real polynomials to parametric polynomials in three dimensions, thus providing an analytical approach to degree reduction. More importantly, we propose a generalization for parametric surfaces which enjoys many of the properties associated with Chebyshev economization.     

A shape preserving interpolant with tension controls

The monotonically and convexly constrained (MONCON) weighted v-spline interpolant is presented, which is the C¹ piecewise cubic solution to a constrained optimization problem. In addition to preserving the local monotonicity and local convexity of the data, the method has tension parameters which can be used to modify the shape of the interpolating function. Local monotonicity constraints are given that don't necessarily force the derivatives to be zero where the data changes from increasing to decreasing.