Why is it possible to detect doped regions of semiconductors in low voltage SEM:a review and update

There is an urgent need for fast, non-destructive and quantitative two-dimensional dopant profiling of modern and future ultra large-scale semiconductor devices. The low voltage scanning electron microscope (LVSEM) has emerged to satisfy this need, in part, whereby it is possible to detect different secondary electron yield values (brightness in the SEM signal) from the p-type to the n-type doped regions as well as different brightness levels from the same dopant type. The mechanism that gives rise to such a secondary electron (SE) contrast effect is not fully understood, however. A review of the different models that have been proposed to explain this SE contrast is given. We report on new experiments that support the proposal that this contrast is due to the establishment of metal-to-semiconductor surface contacts. Further experiments showing the effect of instrument parameters including the electron dose, the scan speeds and the electron beam energy on the SE contrast are also reported. Preliminary results on the dependence of the SE contrast on the existence of a surface structure featuring metal-oxide semiconductor (MOS) are also reported. Copyright © 2005 John Wiley & Sons, Ltd.

Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models

Background - The binding between peptide epitopes and major histocompatibility complex proteins (MHCs) is an important event in the cellular immune response. Accurate prediction of the binding between short peptides and the MHC molecules has long been a principal challenge for immunoinformatics. Recently, the modeling of MHC-peptide binding has come to emphasize quantitative predictions: instead of categorizing peptides as "binders" or "non-binders" or as "strong binders" and "weak binders", recent methods seek to make predictions about precise binding affinities. Results - We developed a quantitative support vector machine regression (SVR) approach, called SVRMHC, to model peptide-MHC binding affinities. As a non-linear method, SVRMHC was able to generate models that out-performed existing linear models, such as the "additive method". By adopting a new "11-factor encoding" scheme, SVRMHC takes into account similarities in the physicochemical properties of the amino acids constituting the input peptides. When applied to MHC-peptide binding data for three mouse class I MHC alleles, the SVRMHC models produced more accurate predictions than those produced previously. Furthermore, comparisons based on Receiver Operating Characteristic (ROC) analysis indicated that SVRMHC was able to out-perform several prominent methods in identifying strongly binding peptides. Conclusion - As a method with demonstrated performance in the quantitative modeling of MHC-peptide binding and in identifying strong binders, SVRMHC is a promising immunoinformatics tool with not inconsiderable future potential.

Solving a Direct Marketing Problem by Three Types of ARTMAP Neural Networks

An important task for a direct mailing company is to detect potential customers in order to avoid unnecessary and unwanted mailing. This paper describes a non-linear method to predict profiles of potential customers using dARTMAP, ARTMAP-IC, and Fuzzy ARTMAP neural networks. The paper discusses advantages of the proposed approaches over similar techniques based on MLP neural networks.

Analysis of Hue Spectra During Storage of Pepper (Capsicum annuum)

Color information is widely used in non-destructive quality assessment of perishable horticultural produces. The presented work investigated color changes of pepper (Capsicum annuum L.) samples received from retail system. The effect of storage temperature (10±2°C and 24±4°C) on surface color and firmness was analyzed. Hue spectra was calculated using sum of saturations. A ColorLite sph850 (400-700nm) spectrophotometer was used as reference instrument. Dynamic firmness was measured on three locations of the surface: tip cap, middle and shoulder. Significant effects of storage conditions and surface location on both color and firmness were observed. Hue spectra responded sensitively to color development of pepper. Prediction model (PLS) was used to estimate dynamic firmess based on hue spectra. Accuracy was very different depending on the location. Firmness of the tip cap was predicted with the highest accuracy (RMSEP=0.0335). On the other hand, middle region cannot be used for such purpose. Due to the simplicity and rapid processing, analysis of hue spectra is a promising tool for evaluation of color in postharvest and food industry.

Responses of sawgrass and spikerush to variation in hydrologic drivers and salinity in Southern Everglades marshes

Aboveground net primary production (ANPP) by the dominant macrophyte and plant community composition are related to the changing hydrologic environment and to salinity in the southern Everglades, FL, USA. We present a new non-destructive ANPP technique that is applicable to any continuously growing herbaceous system. Data from 16 sites, collected from 1998 to 2004, were used to investigate how hydrology and salinity controlled sawgrass (Cladium jamaicense Crantz.) ANPP. Sawgrass live biomass showed little seasonal variation and annual means ranged from 89 to 639 gdw m)2. Mortality rates were 20–35% of live biomass per 2 month sampling interval, for biomass turnover rates of 1.3–2.5 per year. Production by C. jamaicense was manifest primarily as biomass turnover, not as biomass accumulation. Rates typically ranged from 300 to 750 gdw m)2 year)1, but exceeded 1000 gdw m)2 year)1 at one site and were as high as 750 gdw m)2 year)1 at estuarine ecotone sites. Production was negatively related to mean annual water depth, hydroperiod, and to a variable combining the two (depth-days). As water depths and hydroperiods increased in our southern Everglades study area, sawgrass ANPP declined. Because a primary restoration goal is to increase water depths and hydroperiods for some regions of the Everglades, we investigated how the plant community responded to this decline in sawgrass ANPP. Spikerush (Eleocharis sp.) was the next most prominent component of this community at our sites, and 39% of the variability in sawgrass ANPP was explained by a negative relationship with mean annual water depth, hydroperiod, and Eleocharis sp. density the following year. Sawgrass ANPP at estuarine ecotone sites responded negatively to salinity, and rates of production were slow to recover after high salinity years. Our results suggest that ecologists, managers, and the public should not necessarily interpret a decline in sawgrass that may result from hydrologic restoration as a negative phenomenon.

Optimization of wireless power transfer via magnetic resonance in different media

A wide range of non-destructive testing (NDT) methods for the monitoring the health of concrete structure has been studied for several years. The recent rapid evolution of wireless sensor network (WSN) technologies has resulted in the development of sensing elements that can be embedded in concrete, to monitor the health of infrastructure, collect and report valuable related data. The monitoring system can potentially decrease the high installation time and reduce maintenance cost associated with wired monitoring systems. The monitoring sensors need to operate for a long period of time, but sensors batteries have a finite life span. Hence, novel wireless powering methods must be devised. The optimization of wireless power transfer via Strongly Coupled Magnetic Resonance (SCMR) to sensors embedded in concrete is studied here. First, we analytically derive the optimal geometric parameters for transmission of power in the air. This specifically leads to the identification of the local and global optimization parameters and conditions, it was validated through electromagnetic simulations. Second, the optimum conditions were employed in the model for propagation of energy through plain and reinforced concrete at different humidity conditions, and frequencies with extended Debye's model. This analysis leads to the conclusion that SCMR can be used to efficiently power sensors in plain and reinforced concrete at different humidity levels and depth, also validated through electromagnetic simulations. The optimization of wireless power transmission via SMCR to Wearable and Implantable Medical Device (WIMD) are also explored. The optimum conditions from the analytics were used in the model for propagation of energy through different human tissues. This analysis shows that SCMR can be used to efficiently transfer power to sensors in human tissue without overheating through electromagnetic simulations, as excessive power might result in overheating of the tissue. Standard SCMR is sensitive to misalignment; both 2-loops and 3-loops SCMR with misalignment-insensitive performances are presented. The power transfer efficiencies above 50% was achieved over the complete misalignment range of 0°-90° and dramatically better than typical SCMR with efficiencies less than 10% in extreme misalignment topologies.

Flexible pavement layer moduli determination : an adaptive artificial neural network approach

The estimation of pavement layer moduli through the use of an artificial neural network is a new concept which provides a less strenuous strategy for backcalculation procedures. Artificial Neural Networks are biologically inspired models of the human nervous system. They are specifically designed to carry out a mapping characteristic. This study demonstrates how an artificial neural network uses non-destructive pavement test data in determining flexible pavement layer moduli. The input parameters include plate loadings, corresponding sensor deflections, temperature of pavement surface, pavement layer thicknesses and independently deduced pavement layer moduli.

Avaliação das técnicas de soldagem MIG-P CA e MIG-P CC+ aplicadas ao passe de enchimento em liga de alumínio AA5083

For contain beneficial properties, aluminum alloys are gaining more importance in different industrial areas, becoming the subject of study in several academic fields. When related to welding these alloys have some peculiarities that may hinder the union, such as microscopic oxide layer present on the metal surface. The MIG welding process, also known as GMAW, has developed versions that can be effective for welding aluminum. Knowing this, for this paper, two versions of pulsed MIG (CC + and CA) were chosen to evaluate which best suits pass by filling bevel on AA5083 aluminum sheets with 8 and 12 mm thick respectively. Furthermore, two types of wire, ER5087 and ER5183 were evaluated. To evaluate the process and versions of the wires, the high-speed cameras and thermal were used to monitor the metal transfer and the thermal behavior respectively, and the metallographic analysis for macrographic view of the weld beads and non-destructive testing by radiography for observation of possible discontinuities. It was found that the technique of MIG-P CA showed better results ahead of another technique both welding conditions imposed. When connected to the wires, they showed similar results, with uniform cords and seamless

Improved image analysis based corrosion assessment using preprocessing techniques

The importance of non-destructive techniques (NDT) in structural health monitoring programmes is being critically felt in the recent times. The quality of the measured data, often affected by various environmental conditions can be a guiding factor in terms usefulness and prediction efficiencies of the various detection and monitoring methods used in this regard. Often, a preprocessing of the acquired data in relation to the affecting environmental parameters can improve the information quality and lead towards a significantly more efficient and correct prediction process. The improvement can be directly related to the final decision making policy about a structure or a network of structures and is compatible with general probabilistic frameworks of such assessment and decision making programmes. This paper considers a preprocessing technique employed for an image analysis based structural health monitoring methodology to identify sub-marine pitting corrosion in the presence of variable luminosity, contrast and noise affecting the quality of images. A preprocessing of the gray-level threshold of the various images is observed to bring about a significant improvement in terms of damage detection as compared to an automatically computed gray-level threshold. The case dependent adjustments of the threshold enable to obtain the best possible information from an existing image. The corresponding improvements are observed in a qualitative manner in the present study.

Epitaxial growth of visible to infra-red transparent conducting In2O3 nanodot dispersions and reversible charge storage as a Li-ion battery anode

Unique bimodal distributions of single crystal epitaxially grown In2O3 nanodots on silicon are shown to have excellent IR transparency greater than 87% at IR wavelengths up to 4 μm without sacrificing transparency in the visible region. These broadband antireflective nanodot dispersions are grown using a two-step metal deposition and oxidation by molecular beam epitaxy, and backscattered diffraction confirms a dominant (111) surface orientation. We detail the growth of a bimodal size distribution that facilitates good surface coverage (80%) while allowing a significant reduction in In2O3 refractive index. This unique dispersion offers excellent surface coverage and three-dimensional volumetric expansion compared to a thin film, and a step reduction in refractive index compared to bulk active materials or randomly porous composites, to more closely match the refractive index of an electrolyte, improving transparency. The (111) surface orientation of the nanodots, when fully ripened, allows minimum lattice mismatch strain between the In2O3 and the Si surface. This helps to circumvent potential interfacial weakening caused by volume contraction due to electrochemical reduction to lithium, or expansion during lithiation. Cycling under potentiodynamic conditions shows that the transparent anode of nanodots reversibly alloys lithium with good Coulombic efficiency, buffered by co-insertion into the silicon substrate. These properties could potentially lead to further development of similarly controlled dispersions of a range of other active materials to give transparent battery electrodes or materials capable of non-destructive in situ spectroscopic characterization during charging and discharging.

Lattice Engineering of III-Nitride Heterostructures and Their Applications

III-Nitride materials have recently become a promising candidate for superior applications over the current technologies. However, certain issues such as lack of native substrates, and high defect density have to be overcome for further development of III-Nitride technology. This work presents research on lattice engineering of III-Nitride materials, and the structural, optical, and electrical properties of its alloys, in order to approach the ideal material for various applications. We demonstrated the non-destructive and quantitative characterization of composition modulated nanostructure in InAlN thin films with X-ray diffraction. We found the development of the nanostructure depends on growth temperature, and the composition modulation has impacts on carrier recombination dynamics. We also showed that the controlled relaxation of a very thin AlN buffer (20 ~ 30 nm) or a graded composition InGaN buffer can significantly reduce the defect density of a subsequent epitaxial layer. Finally, we synthesized an InAlGaN thin films and a multi-quantum-well structure. Significant emission enhancement in the UVB range (280 – 320 nm) was observed compared to AlGaN thin films. The nature of the enhancement was investigated experimentally and numerically, suggesting carrier confinement in the In localization centers.

Decision-Making in the Primate Brain

Making decisions is fundamental to everything we do, yet it can be impaired in various disorders and conditions. While research into the neural basis of decision-making has flourished in recent years, many questions remain about how decisions are instantiated in the brain. Here we explored how primates make abstract decisions and decisions in social contexts, as well as one way to non-invasively modulate the brain circuits underlying decision-making. We used rhesus macaques as our model organism. First we probed numerical decision-making, a form of abstract decision-making. We demonstrated that monkeys are able to compare discrete ratios, choosing an array with a greater ratio of positive to negative stimuli, even when this array does not have a greater absolute number of positive stimuli. Monkeys’ performance in this task adhered to Weber’s law, indicating that monkeys—like humans—treat proportions as analog magnitudes. Next we showed that monkeys’ ordinal decisions are influenced by spatial associations; when trained to select the fourth stimulus from the bottom in a vertical array, they subsequently selected the fourth stimulus from the left—and not from the right—in a horizontal array. In other words, they begin enumerating from one side of space and not the other, mirroring the human tendency to associate numbers with space. These and other studies confirmed that monkeys’ numerical decision-making follows similar patterns to that of humans, making them a good model for investigations of the neurobiological basis of numerical decision-making.

We sought to develop a system for exploring the neuronal basis of the cognitive and behavioral effects observed following transcranial magnetic stimulation, a relatively new, non-invasive method of brain stimulation that may be used to treat clinical disorders. We completed a set of pilot studies applying offline low-frequency repetitive transcranial magnetic stimulation to the macaque posterior parietal cortex, which has been implicated in numerical processing, while subjects performed a numerical comparison and control color comparison task, and while electrophysiological activity was recorded from the stimulated region of cortex. We found tentative evidence in one paradigm that stimulation did selectively impair performance in the number task, causally implicating the posterior parietal cortex in numerical decisions. In another paradigm, however, we manipulated the subject’s reaching behavior but not her number or color comparison performance. We also found that stimulation produced variable changes in neuronal firing and local field potentials. Together these findings lay the groundwork for detailed investigations into how different parameters of transcranial magnetic stimulation can interact with cortical architecture to produce various cognitive and behavioral changes.

Finally, we explored how monkeys decide how to behave in competitive social interactions. In a zero-sum computer game in which two monkeys played as a shooter or a goalie during a hockey-like “penalty shot” scenario, we found that shooters developed complex movement trajectories so as to conceal their intentions from the goalies. Additionally, we found that neurons in the dorsolateral and dorsomedial prefrontal cortex played a role in generating this “deceptive” behavior. We conclude that these regions of prefrontal cortex form part of a circuit that guides decisions to make an individual less predictable to an opponent.

A stereo-image analysis JAVA software with links to executable and source code

Scientists planning to use underwater stereoscopic image technologies are often faced with numerous problems during the methodological implementations: commercial equipment is too expensive; the setup or calibration is too complex; or the imaging processing (i.e. measuring objects in the stereo-images) is too complicated to be performed without a time-consuming phase of training and evaluation. The present paper addresses some of these problems and describes a workflow for stereoscopic measurements for marine biologists. It also provides instructions on how to assemble an underwater stereo-photographic system with two digital consumer cameras and gives step-by-step guidelines for setting up the hardware. The second part details a software procedure to correct stereo-image pairs for lens distortions, which is especially important when using cameras with non-calibrated optical units. The final part presents a guide to the process of measuring the lengths (or distances) of objects in stereoscopic image pairs. To reveal the applicability and the restrictions of the described systems and to test the effects of different types of camera (a compact camera and an SLR type), experiments were performed to determine the precision and accuracy of two generic stereo-imaging units: a diver-operated system based on two Olympus Mju 1030SW compact cameras and a cable-connected observatory system based on two Canon 1100D SLR cameras. In the simplest setup without any correction for lens distortion, the low-budget Olympus Mju 1030SW system achieved mean accuracy errors (percentage deviation of a measurement from the object's real size) between 10.2 and -7.6% (overall mean value: -0.6%), depending on the size, orientation and distance of the measured object from the camera. With the single lens reflex (SLR) system, very similar values between 10.1% and -3.4% (overall mean value: -1.2%) were observed. Correction of the lens distortion significantly improved the mean accuracy errors of either system. Even more, system precision (spread of the accuracy) improved significantly in both systems. Neither the use of a wide-angle converter nor multiple reassembly of the system had a significant negative effect on the results. The study shows that underwater stereophotography, independent of the system, has a high potential for robust and non-destructive in situ sampling and can be used without prior specialist training.