Intrinsic Dependency Research Articles

Practical design of a diffusion-type time-temperature indicator with intrinsic low temperature dependency

A diffusion-type time-temperature indicator (TTI) is known to have relatively low temperature dependency, which is an inherent weakness that causes an inevitable prediction error of food shelf-life: under- or over-prediction. In this study, a TTI design method was developed to avoid the undesired overprediction. A polydiacetylene/silica nanocomposite (PDA/SiO2 NC) was used as the color-developing substance, which was loaded on the diffusion path of a microporous strip, with Tween 20 as the moving substance. When the Tween 20 reached the test line of the PDA/SiO2 NC, the line transitioned from blue to red, indicating the TTI endpoint. A principal design factor was used to accurately locate the test line. Four TTIs (TTI5°C, TTI10°C, TTI15°C, and TTI25°C) were designed in combination with the various test line locations, by matching the TTI endpoints with the food deterioration time during storage at 5, 10, 15 and 25 °C, respectively. Wheatgrass juice, a healthy drink with a relatively short shelf-life at 5 °C of about 5 days, was used as the food specimen. During storage at 5–25 °C, TTI25°C underpredicted the juice shelf-life, such that the TTI reached the endpoint before the wheatgrass juice attained the deterioration point. However, the other TTIs did not always underpredict the juice shelf-life. The optimal diffusion-type TTI design was found to locate the test line of the PDA/SiO2 NC matching the shelf-life of the tested food at the highest possible temperature during storage.

Improving repeatability of capillary electrophoresis\u2014a critical comparison of ten different capillary inner surfaces and three criteria of peak identification

A poor repeatability of migration times caused by the fluctuations of electroosmotic flow (EOF) is an inherent weakness of capillary electrophoresis. Most researchers endeavor to prevent this problem using relative migration times or various capillary coatings which are expensive and not easy in comparison. Herein, we present an original approach to this problem: we apply a model sample designed to induce significant EOF instability, in order to critically compare ten capillary types with different physicochemical characteristics. Moreover, we accompany capillary modification with the evaluation of various criteria of peak identification: migration time, migration times ratio, and electrophoretic mobility. Our results show a great effectiveness of a dynamic coating in the stabilization of migration times, with the average RSD(%) value reduced from 3.5% (bare silica capillary) down to 0.5%. The good outcomes were also obtained for the surfactant-modified silica and amine capillaries. For the capillaries exhibiting significant instability of EOF, electrophoretic mobility turned out to be a more universal and reliable criterion of peak identification than relative migration time. It can be explained by an intrinsic dependency of migration times ratio on EOF change, which should always be considered during the selection of an internal standard.

Video Super-Resolution via Bidirectional Recurrent Convolutional Networks.

Super resolving a low-resolution video, namely video super-resolution (SR), is usually handled by either single-image SR or multi-frame SR. Single-Image SR deals with each video frame independently, and ignores intrinsic temporal dependency of video frames which actually plays a very important role in video SR. Multi-Frame SR generally extracts motion information, e.g., optical flow, to model the temporal dependency, but often shows high computational cost. Considering that recurrent neural networks (RNNs) can model long-term temporal dependency of video sequences well, we propose a fully convolutional RNN named bidirectional recurrent convolutional network for efficient multi-frame SR. Different from vanilla RNNs, 1) the commonly-used full feedforward and recurrent connections are replaced with weight-sharing convolutional connections. So they can greatly reduce the large number of network parameters and well model the temporal dependency in a finer level, i.e., patch-based rather than frame-based, and 2) connections from input layers at previous timesteps to the current hidden layer are added by 3D feedforward convolutions, which aim to capture discriminate spatio-temporal patterns for short-term fast-varying motions in local adjacent frames. Due to the cheap convolutional operations, our model has a low computational complexity and runs orders of magnitude faster than other multi-frame SR methods. With the powerful temporal dependency modeling, our model can super resolve videos with complex motions and achieve well performance.

Failure patterns in operating systems: An exploratory and observational study

Sophisticated critical computer applications need to run on top of operating system (OS) software. Given the natural intrinsic dependency of user applications on the OS software, OS failures can severely impact even the most reliable applications. Thus, it is essential to understand how OS failures occur in order to improve software reliability. In this paper, we present an exploratory and observational study on OS failure patterns. We analyze 7007 real OS failures collected from 566 computers used in different workplaces. We start with a general characterization of the failure dataset examined in this study, where interesting findings are presented, e.g., the most frequent failure types per period of a day and per different workplaces. Next, we investigate the existence of failure patterns. For this purpose, we introduce an OS failure pattern discovery protocol that identifies failure patterns exhibiting consistency across different computers used in the same as well as different workplaces. In total, we discovered 45 failure patterns with 153,511 occurrences. Based on these patterns, we found that the most prevalent failures were related to the software updates of the OS components. The main causes of these failures involved infrastructural and environmental factors such as disk-space unavailability and concurrent execution of OS services. Empirical evidence of time-correlated failures of these OS components is also discussed in this paper. Other findings include the OS components that contributed more to create the discovered failure patterns and the most prevalent combination of failure events and their temporal order. This study aims at to contribute to a better understanding of the mechanisms behind OS failures.

An Organelle Correlation-Guided Feature Selection Approach for Classifying Multi-Label Subcellular Bio-Images.

Nowadays, with the advances in microscopic imaging, accurate classification of bioimage-based protein subcellular location pattern has attracted as much attention as ever. One of the basic challenging problems is how to select the useful feature components among thousands of potential features to describe the images. This is not an easy task especially considering there is a high ratio of multi-location proteins. Existing feature selection methods seldom take the correlation among different cellular compartments into consideration, and thus may miss some features that will be co-important for several subcellular locations. To deal with this problem, we make use of the important structural correlation among different cellular compartments and propose an organelle structural correlation regularized feature selection method CSF (Common-Sets of Features) in this paper. We formulate the multi-label classification problem by adopting a group-sparsity regularizer to select common subsets of relevant features from different cellular compartments. In addition, we also add a cell structural correlation regularized Laplacian term, which utilizes the prior biological structural information to capture the intrinsic dependency among different cellular compartments. The CSF provides a new feature selection strategy for multi-label bio-image subcellular pattern classifications, and the experimental results also show its superiority when comparing with several existingalgorithms.

Performance modeling and optimization of parallel LU-SGS on many-core processors for 3D high-order CFD simulations

As a typical Gauss---Seidel method, the inherent strong data dependency of lower-upper symmetric Gauss---Seidel (LU-SGS) poses tough challenges for shared-memory parallelization. On early multi-core processors, the pipelined parallel LU-SGS approach achieves promising scalability. However, on emerging many-core processors such as Xeon Phi, experience from our in-house high-order CFD program show that the parallel efficiency drops dramatically to less than 25%. In this paper, we model and analyze the performance of the pipelined parallel LU-SGS algorithm, present a two-level pipeline (TL-Pipeline) approach using nested OpenMP to further exploit fine-grained parallelisms and mitigate the parallel performance bottlenecks. Our TL-Pipeline approach achieves 20% performance gains for a regular problem $$(256\times 256\times 256)$$(256×256×256) on Xeon Phi. We also discuss some practical problems including domain decomposition and algorithm parameters tuning for realistic CFD simulations. Generally, our work is applicable to the shared-memory parallelization of all Gauss---Seidel like methods with intrinsic strong data dependency.

Arterial Stiffness: Going a Step Beyond.

Interest in arterial stiffness has been fueled by the scientific and clinical implications of its "vicious cycle" relationship with aging and systolic blood pressure. In physical terms, stiffness is the slope of the relationship between an artery's distending pressure and its cross-sectional area or volume. Pulse wave velocity (PWV, in m/s), the most common arterial stiffness indicator, is usually measured by the foot-to-foot time and distance method and is proportional to [stiffness × area (or volume)]1/2 at a given pressure. Its intrinsic pressure dependency and other flaws in current PWV methods limit its utility. In contrast, the arterial stiffness-arterial pressure relationship is near-linear, with a slope β, the exponent of the curvilinear arterial pressure-arterial volume relationship. The concept of arterial stiffening is related to β and describes a more functionally relevant aspect of arterial behavior: the change in stiffness for a given change in pressure. Arterial stiffening can be estimated from the variability of within-individual BP measurements (24-h ambulatory, home BP, or BP measured at different arm heights) and can be expressed as the pulse stiffening ratio (PSR) = [systolic stiffness]/[diastolic stiffness] or the ambulatory arterial stiffness index (AASI or its symmetric form, sAASI). High arterial stiffness (PWV) and stiffening (β, stiffness index, cardio-ankle vascular index, AASI, and PSR) are associated with increased cardiovascular disease risk, but it remains unclear whether these indicators are useful in improving medical care quality; the standard of care remains stringent BP control.

Exploratory Analysis on Failure Causes in a Mass-Market Operating System

Empirical studies in software reliability have predominantly focused on end-user applications. Given the intrinsic dependency of user programs on the operating system (OS) software, OS failures can severely impact even the most reliable applications. Therefore, it is a major requirement to understand how OS failures occur in order to improve software reliability as a whole. In this paper, we present an exploratory study on OS failure causes, based on 7,007 real failure records collected from different computers running a mass-market operating system. We performed quantitative and qualitative analyses to investigate different properties of the OS failures analyzed. The findings indicate that OS services failed more than any other OS failure category. Empirical evidences confirmed the presence of failure correlation in the sample, where both cross-correlation and autocorrelation were found; in particular, causal relationship between different operating system failures was observed.

Is dexmedetomidine a favorable agent for cerebral hemodynamics?

Is dexmedetomidine a favorable agent for cerebral hemodynamics?

Reduced-rank multi-label classification

Multi-label classification is a natural generalization of the classical binary classification for classifying multiple class labels. It differs from multi-class classification in that the multiple class labels are not exclusive. The key challenge is to improve the classification accuracy by incorporating the intrinsic dependency structure among the multiple class labels. In this article we propose to model the dependency structure via a reduced-rank multi-label classification model, and to enforce a group lasso regularization for sparse estimation. An alternative optimization scheme is developed to facilitate the computation, where a constrained manifold optimization technique and a gradient descent algorithm are alternated to maximize the resultant regularized log-likelihood. Various simulated examples and two real applications are conducted to demonstrate the effectiveness of the proposed method. More importantly, its asymptotic behavior is quantified in terms of the estimation and variable selection consistencies, as well as the model selection consistency via the Bayesian information criterion.

Stochastic Modeling of Organic Additives in Cu Electroplating

Organic additives used in Cu electroplating for IC interconnects have been studied extensively due to their pivotal roles in the void-free filling of recessed features. The suppressive additives are typically polymers or co-polymers with variable molecular weight (MW). The properties of these additives, as well as their interaction with accelerator, vary with the monomer type and the MW. As the additives are typically treated as indivisible molecules in the analysis of the filling mechanism, these variations are typically quantified by the difference in some coefficients that characterize the additive behaviors, such as adsorption / desorption rates and suppression strength. As an example, polyethylene glycol (PEG) with a larger MW would have a higher adsorption rate and exhibit stronger suppression effect than PEG with a smaller MW. However, since these large molecules consist of multiple identical building blocks from the polymerization of one or more monomer species, the behavior of the molecule as a whole depends on the number and type of the monomers. In order to understand such an intrinsic dependency and the resulting differences in additive properties, stochastic modeling was applied in the study of suppressor additive and its interaction with accelerator [1]. Using PEG and SPS as the model chemicals, a stochastic model was developed to simulate the transient processes in Cu electroplating, e.g. cyclic voltammogram (CV) under various conditions. Simulations were performed for both suppressor-only cases and suppressor-accelerator interactions. The dependency of PEG adsorption / desorption and PEG-SPS interaction on various factors, including bath composition, scan rate and molecular weight, was simulated and compared with the corresponding experimental measurements. An overall good qualitative match was shown in the comparisons. Figure 1 shows simulated CVs under two very different conditions. At higher SPS/Cl- concentrations, case (a) demonstrates the PEG-SPS interaction, which has been known to be important for the super-conformal filling of trenches [2, 3]. At lower SPS / Cl-concentrations, case (b) demonstrates the critical desorption behavior of PEG as a suppressor, which has been shown to be important for the fast bottom-up type filling of high aspect ratio TSVs in damascene copper plating [4]. Since the proposed model provides a unified approach to simulate both the suppress-accelerator interaction and the critical desorption behavior of suppressors, it enables the development of general-purpose multi-scale simulation programs for the filling of various recessed features within a wide length-scale range covering both the Damascene interconnects and TSVs.

LA BÚSQUEDA DE UN DESARROLLO SOSTENIBLE: LA NECESIDAD DE REDISEÑAR LOS PRODUCTOS MANUFACTURADOS

<p>La búsqueda de un desarrollo que sea sostenible ambientalmente implica aceptar la realidad de un mundo de recursos finitos y la necesidad urgente de repensar nuestros hábitos de consumo y, más aún, nuestros procesos manufactureros. Ya no podemos darnos el lujo de un proceso lineal de producción en el cual se extraen recursos, se procesan, se empacan, de distribuyen, se consumen, y se descartan. Este proceso genera dos graves problemas: escasez de recursos (y los picos petroleros, de minerales raros, de tierra agrícola e incluso agua lo demuestran con creces) y enormes problemas en la gestión de grandes y siempre crecientes desperdicios, algunos muy tóxico y contaminación. Esa concepción corresponde a una etapa adolescente en nuestra evolución colectiva como humanidad, de una creencia ciega en un crecimiento económico y demandas humanas ilimitadas, y reducida preocupación por los impactos ambientales de los procesos productivos. Hay que rediseñar los productos manufacturados para que, en su diseño, este previsto que al terminar su vida útil puedan ser todos sus componentes reutilizados o que sean biodegradables de manera natural. Al comprar un televisor uno no compraría la materia prima que lo compone, sino el servicio que ofrece y al terminar su vida útil, la empresa que lo produce debe retomarlo y ver cómo hace para reutilizar sus componentes. Varios países europeos están moviéndose en esa dirección con legislación que obliga a las empresas a retomar sus productos. Al hacer eso, entraríamos a una etapa de mayor madurez y responsabilidad en nuestros procesos manufactureros, de menor orgullo, más humildad y de reconocimiento de nuestra intrínseca dependencia de los ciclos vitales que sustentan la vida en la tierra. Tal vez sea uno de los principales desafíos de la era moderna. El libro de Braungart y McDonell, “De la Cuna a la Cuna” es, así como lo fue “Lo Pequeño es Hermoso” o “La Primavera Silenciosa”, un libro pionero en este sentido y un libro de referencia obligatoria para quienes estén interesados en la búsqueda de un desarrollo que sea sostenible ambientalmente.</p><p><strong>Palabras claves:</strong> Producción lineal, Circular, Diseño tosco, Vida útil, Etapa adolescente y madurez.</p>

Intrinsic climate dependency of ecosystem light and water-use-efficiencies across Australian biomes

The sensitivity of ecosystem gross primary production (GPP) to availability of water and photosynthetically active radiation (PAR) differs among biomes. Here we investigated variations of ecosystem light-use-efficiency (eLUE: GPP/PAR) and water-use-efficiency (eWUE: GPP/evapotranspiration) among seven Australian eddy covariance sites with differing annual precipitation, species composition and temperature. Changes to both eLUE and eWUE were primarily correlated with atmospheric vapor pressure deficit (VPD) at multiple temporal scales across biomes, with minor additional correlations observed with soil moisture and temperature. The effects of leaf area index on eLUE and eWUE were also relatively weak compared to VPD, indicating an intrinsic dependency of eLUE and eWUE on climate. Additionally, eLUE and eWUE were statistically different for biomes between summer and winter, except eWUE for savannas and the grassland. These findings will improve our understanding of how light- and water-use traits in Australian ecosystems may respond to climate change.

Direct Sound Radiation Testing on a Mounted Car Engine

For (benchmark) tests it is not only useful to study the acoustic performance of the whole vehicle, but also to assess separate components such as the engine. Reflections inside the engine bay bias the acoustic radiation estimated with sound pressure based solutions. Consequently, most current methods require dismounting the engine from the car and installing it in an anechoic room to measure the sound emitted. However, this process is laborious and hard to perform. In this paper, two particle velocity based methods are proposed to characterize the sound radiated from an engine while it is still installed in the car. Particle velocity sensors are much less affected by reflections than sound pressure microphones when the measurements are performed near a radiating surface due to the particle velocity's vector nature, intrinsic dependency upon surface displacement and directivity of the sensor. Therefore, the engine does not have to be disassembled, which saves time and money. An array of special high temperature particle velocity probes is used to measure the radiation simultaneously at many positions near the engine of a compact class car. The particularities of these probes, the mountings used, and the actions taken to cope with disturbances such as airflows are described in this paper. The effective sound pressure is calculated with a particle velocity based transfer path analysis method and a novel sound power based method. To validate these techniques, the data obtained is compared to the results acquired in an anechoic room with a dismounted engine. It is shown that similar results can be obtained with both methods but that the sound power based methodology seems more practical. It is a straightforward and fast approach to characterize the average sound pressure level at certain distance.

Nonlinear bending and post-buckling of extensible microscale beams based on modified couple stress theory

This study proposes a computationally efficient approach to nonlinear bending and thermal post-buckling problems in Euler–Bernoulli microbeams based on modified couple stress theory under geometrically accurate relationships. The governing equations, which consider the size effect and the axis extensibility, are formulated via the equilibrium of an infinitesimal element. The proposed model, which encompasses the size-independent and Von Kármán nonlinear theory, is solved using the shooting technique after transformation into a two-point boundary value problem. The proposed method was validated based on comparisons with several case studies using existing simulations. The influences of the length scale parameter and the Poisson ratio on the bending and thermal post-buckling behaviors of microbeams are discussed in detail. The numerical results show that the intrinsic size dependency of the material and the Poisson ratio make the microbeam behave in a relatively stiff manner, thereby leading to smaller deformations and greater increases in the buckling temperature.

Validation of Automatic Contour Propagation for 4D Treatment Planning Using Multiple Metrics

The aim of this work is to provide insights into multiple metrics clinical validation of deformable image registration and contour propagation methods in 4D lung radiotherapy planning. The following indices were analyzed and compared: Volume Difference (VD), Dice Similarity Coefficient (DSC), Positive Predictive Value (PPV) and Surface Distances (SD). The analysis was performed on three patient datasets, using as reference a ground-truth volume generated by means of Simultaneous Truth And Performance Level Estimation (STAPLE) algorithm from the outlines of five experts. Significant discrepancies in the quality assessment provided by the different metrics in all the examined cases were found. Metrics sensitivity was more evident in presence of image artifacts and particularly for tubular anatomical structures, such as esophagus or spinal cord. Volume Differences did not account for position and DSC exhibited criticalities due to its intrinsic symmetry (i.e. over- and under-estimation of the reference contours cannot be discriminated) and dependency on the total volume of the structure. PPV analysis showed more robust performance, as each voxel concurs to the classification of the propagation, but was not able to detect inclusion of propagated and ground-truth volumes. Mesh distances could interpret the actual shape of the structures, but might report higher mismatches in case of large local differences in the contour surfaces. According to our study, the combination of VD and SD for the validation of contour propagation algorithms in 4D could provide the necessary failure detection accuracy.

One-, two-, and three-electron bonding: An “in vitro” theoretical study using noninteger nuclear charges evidences the crucial role of electronegativity in the strength of symmetrical bonds

Fictitious hydrogen atoms H*A of variable nuclear charge 0.5 ≤ ZA ≤ 2 (and thus of variable electronegativity) are used to study the intrinsic dependency of chemical bonding on electronegativity. Dissociation energy and equilibrium distance are reported for symmetrical 1-, 2- and 3-electron H*AH*A systems and 2-electron dissymmetrical H*A-H ones. Dealing with symmetrical systems, the strongest two-electron bonds are found for ZA ≈ 1.2. Oneelectron and three-electron strongest bonds occur respectively with low (ca. 0.7) and high (ca. 1.7) ZA values and can become stronger than the corresponding 2-electron system. Comparison with data on real systems leads to conclude that electronegativity is a prevailing atomic property in the control of the dissociation energy of symmetrical 1-, 2- and 3-electron bonds. A simplified mathematical model at Hartree-Fock or Heitler-London level with a minimal basis set reproduces these trends semi-quantitatively and provides the overall shape of the dissociation curves. Finally some points are qualitatively discussed from MO analysis, which emphasize the dependence of the bonding/antibonding properties on the nucleus charge ZA and their occupancy number. © 2011 Wiley Periodicals, Inc. Int J Quantum Chem, 2011

The medicine is worse than the disease: Comment on Delhey and Kohler’s proposal to measure inequality in happiness using ‘instrument-effect-corrected’ standard deviations

Inequality of happiness in nations can be measured using the standard deviation of responses to surveys questions. The standard-deviation is not quite independent of the mean, being zero when everybody is maximally happy or unhappy while the possible value of the standard deviation is highest when the mean is in the middle of the response scale. Delhey and Kohler see this intrinsic dependency as a problem and propose two ways to compute ‘corrected’ standard deviations. I advise against this medicine. One reason is that there is no real disease, since the presumed problem does not occur with commonly used numerical rating scales of 10 or more steps. The second reason is that one of Delhey and Kohler’s medicines have side effects, their first correction affects the mean and their second correction is based on implausible assumptions. A third reason is that there are better ways to estimate the effect happiness-inequality net happiness-level. Partialling out mean happiness did not affect the non-correlation between inequality of income and inequality of happiness in an analysis of 116 nations.

Tuning the dependency between stiffness and permeability of a cell encapsulating hydrogel with hydrophilic pendant chains

The mechanical stiffness of a hydrogel plays a significant role in regulating the phenotype of cells that adhere to its surface. However, the effect of hydrogel stiffness on cells cultured within its matrix is not well understood, because of the intrinsic inverse dependency between the permeability and stiffness of hydrogels. This study therefore presents an advanced biomaterial design strategy to decrease the inverse dependency between permeability and stiffness of a cell encapsulating hydrogel. Hydrogels were made by cross-linking poly(ethylene glycol) diacrylate (PEGDA) and poly(ethylene glycol) monoacrylate (PEGMA), with PEGMA acting as a pendant polymer chain. Increasing the mass fraction of PEGMA while keeping the total polymer concentration constant led to a decrease in the elastic modulus ( E) of the hydrogel, but caused a minimal increase in the swelling ratio ( Q). The size and hydrophobicity of the end groups of pendant PEG chains further fine tuned the dependency between Q and E of the hydrogel. Pure PEGDA hydrogels with varying molecular weights, which show the same range of E but a much greater range of Q, were used as a control. Fibroblasts encapsulated in PEGDA–PEGMA hydrogels displayed more significant biphasic dependencies of cell viability and vascular endothelial growth factor (VEGF) expression on E than those encapsulated in pure PEGDA hydrogels, which were greatly influenced by Q. Overall, the hydrogel design strategy presented in this study will be highly useful to better regulate the phenotype and ultimately improve the therapeutic efficacy of a wide array of cells used in various biology studies and clinical settings.

Algorithm analysis and architecture design for rate distortion optimized mode decision in high definition AVS video encoder

There are abundant intra and inter prediction modes in the AVS video coding standard. Rate distortion optimized mode decision can fully utilize this flexibility to improve the spatio-temporal prediction efficiency and maximize the coding efficiency. However, the implementation complexity is dramatically high due to huge throughput burden. Hardware oriented mode decision algorithm is tailored for VLSI implementation in this work for high definition video coding. Mode preselection is employed to alleviate the dramatic throughout burden. Also, intelligent pipeline scheduling mechanism is proposed to break the intrinsic data dependency in intra prediction, which is directly related with mode decision. The proposed simplified algorithm is well-suited for hardware implementation with small performance penalty. Finally, the VLSI architecture is proposed with good trade off between circuit consumption and rate distortion performance.