An electronic component is provided, which includes a substrate having opposite first and second surfaces and an antenna structure combined with the substrate. The antenna structure has at least a first extending portion disposed on the first surface of the substrate, at least a second extending portion disposed on the second surface of the substrate, and a plurality of connecting portions disposed in the substrate for electrically connecting the first extending portion and the second extending portion. Any adjacent ones of the connecting portions are connected through one of the first extending portion and the second extending portion. As such, the antenna structure becomes three-dimensional. The present invention does not need to provide an additional region on the substrate for disposing the antenna structure, thereby reducing the width of the substrate so as to meet the miniaturization requirement of the electronic component.

A force detector includes a first substrate, a second substrate, a circuit board provided between the first substrate and the second substrate, and an element mounted on the circuit board and outputting a signal in response to an external force, wherein a hole is formed in the circuit board at a location where the element is placed, and a first convex part inserted into the hole and protruding toward the element is provided on the first substrate. Further, the element is placed within a periphery of the first convex part as seen from a direction perpendicular to the first substrate.

Embodiments of the disclosure relate to ultrasonic inspection of turbine components. In one embodiment, a method for ultrasonic inspection of a turbine component can include mounting at least one array of transducer elements to the turbine component, (a) separately pulsing a transducer element of the at least one array of transducer elements to transmit a signal to the turbine component, (b) capturing reflected signals from the turbine component at each transducer element in the at least one array of transducer elements, repeating (a) and (b) for each of the other transducer elements in the at least one array of transducer elements, maintaining a constant relative position of the array of transducer elements with respect to the turbine component, analyzing the captured reflected signals using a computer, generating an image of the interior volume of the turbine component by reconstruction of the captured reflected signals and based at least in part on detecting an anomaly in the image of the interior volume of the turbine component, identifying at least one defect or failure in the turbine component.

An electronic circuit for amplifying signals with two components in phase quadrature, which includes: a feedback amplifier with a feedback capacitor; a switch that drives charging and discharging of the feedback capacitor; an additional capacitor; and a coupling circuit, which alternatively connects the additional capacitor in parallel to the feedback capacitor or else decouples the additional capacitor from the feedback capacitor. The switch opens at a first instant, where a first one of the two components assumes a first zero value; the coupling circuit decouples the additional capacitor from the feedback capacitor in a way synchronous with a second instant, where the first component assumes a second zero value.

A ceramic electronic component includes an interior part and an exterior part. The interior part includes an interior part dielectric layer and an internal electrode layer. The exterior part includes an exterior part dielectric layer. The exterior part is positioned outside the interior part along a laminating direction thereof. The interior part dielectric layer and the exterior part dielectric layer respectively contain barium titanate as a main component. β−α≧0.20 and α/β≦0.88 are satisfied, where α mol part and β mol part are respectively an amount of a rare earth element contained in the interior and exterior part dielectric layers, provided that an amount of barium titanate contained in the interior and exterior part dielectric layers is respectively 100 mol parts in terms of BaTiO3.

A ceramic electronic component includes a dielectric layer and an electrode layer. The dielectric layer contains a plurality of ceramic particles and grain boundary phases present therebetween. A main component of the ceramic particles is barium titanate. An average thickness of the grain boundary phases is 1.0 nm or more. A thickness variation σ of the grain boundary phases is 0.1 nm or less.

A multilayer ceramic electronic component includes a laminated body including dielectric layers and internal electrode layers, and first and second external electrodes. The laminated body further includes a first conductor layer, a first insulating coating layer, a second conductor layer, and a second insulating coating layer. The surface of the first conductor layer closer to a first end surface is partially connected to the first external electrode. The surface of the second conductor layer closer to a second end surface is partially connected to the second external electrode.

An enhanced airflow chassis system includes a component chassis that defines a chassis enclosure including a chassis entrance and component slots. First component carriers are mounted to first components and positioned in each of the component slots. Each first component carrier defines first component carrier airflow apertures that direct airflow entering the chassis entrance to the first component mounted to that first component carrier. A backplane located in the chassis enclosure opposite the component slots from the chassis entrance defines backplane airflow apertures and includes a component connector located adjacent each of the component slots that is connected to the first component mounted to the component carrier positioned in that component slot. A chassis venting member positioned between at least two of the component slots defines chassis venting member airflow apertures that direct airflow entering the chassis entrance through the chassis enclosure to a subset of the backplane airflow apertures.

A component for a gas turbine engine including a gas path wall having a first surface and a second surface. A cooling hole extends through the gas path wall from an inlet in the first surface through a transition to an outlet in the second surface. Cusps are formed on the transition.

Apparatuses and methods for applying a transfer material onto the surface of an article are disclosed, including apparatuses and methods of transfer printing on and/or decorating three-dimensional articles, as well as the articles printed and/or decorated thereby. In some cases, the apparatuses and methods involve providing a deposition device, such as a printing device; providing a transfer component; depositing a material onto a portion of the transfer component with the deposition device; modifying the portion of the transfer component with the transfer material thereon to conform the transfer component to at least a portion of the surface of the three-dimensional article; and transferring the transfer material onto the surface of the article.

Roles & Responsibility: Perform design, and analysis of magnetic components for high voltage and or high power systems Create and document models for the analysis of the magnetic components Create detailed component design, test and manufacturing documentation for magnetic components D

Lawrence E. Ostrowski
Jun 1, 2002; 1:451-465
Research

Jan Pearson
Apr 1, 2001; 14:
Articles

Sperm head shaping is a key event in spermiogenesis and is tightly controlled via the acrosome–manchette network. Linker of nucleoskeleton and cytoskeleton (LINC) complexes consist of Sad1 and UNC84 domain–containing (SUN) and Klarsicht/ANC-1/Syne-1 homology (KASH) domain proteins and form conserved nuclear envelope bridges implicated in transducing mechanical forces from the manchette to sculpt sperm nuclei into a hook-like shape. However, the role of LINC complexes in sperm head shaping is still poorly understood. Here we assessed the role of SUN3, a testis-specific LINC component harboring a conserved SUN domain, in spermiogenesis. We show that CRISPR/Cas9-generated Sun3 knockout male mice are infertile, displaying drastically reduced sperm counts and a globozoospermia-like phenotype, including a missing, mislocalized, or fragmented acrosome, as well as multiple defects in sperm flagella. Further examination revealed that the sperm head abnormalities are apparent at step 9 and that the sperm nuclei fail to elongate because of the absence of manchette microtubules and perinuclear rings. These observations indicate that Sun3 deletion likely impairs the ability of the LINC complex to transduce the cytoskeletal force to the nuclear envelope, required for sperm head elongation. We also found that SUN3 interacts with SUN4 in mouse testes and that the level of SUN4 proteins is drastically reduced in Sun3-null mice. Altogether, our results indicate that SUN3 is essential for sperm head shaping and male fertility, providing molecular clues regarding the underlying pathology of the globozoospermia-like phenotype.

Sperm head shaping is a key event in spermiogenesis and is tightly controlled via the acrosome–manchette network. Linker of nucleoskeleton and cytoskeleton (LINC) complexes consist of Sad1 and UNC84 domain–containing (SUN) and Klarsicht/ANC-1/Syne-1 homology (KASH) domain proteins and form conserved nuclear envelope bridges implicated in transducing mechanical forces from the manchette to sculpt sperm nuclei into a hook-like shape. However, the role of LINC complexes in sperm head shaping is still poorly understood. Here we assessed the role of SUN3, a testis-specific LINC component harboring a conserved SUN domain, in spermiogenesis. We show that CRISPR/Cas9-generated Sun3 knockout male mice are infertile, displaying drastically reduced sperm counts and a globozoospermia-like phenotype, including a missing, mislocalized, or fragmented acrosome, as well as multiple defects in sperm flagella. Further examination revealed that the sperm head abnormalities are apparent at step 9 and that the sperm nuclei fail to elongate because of the absence of manchette microtubules and perinuclear rings. These observations indicate that Sun3 deletion likely impairs the ability of the LINC complex to transduce the cytoskeletal force to the nuclear envelope, required for sperm head elongation. We also found that SUN3 interacts with SUN4 in mouse testes and that the level of SUN4 proteins is drastically reduced in Sun3-null mice. Altogether, our results indicate that SUN3 is essential for sperm head shaping and male fertility, providing molecular clues regarding the underlying pathology of the globozoospermia-like phenotype.

Gökhan S Hotamisligil
Nov 1, 1994; 43:1271-1278
Perspectives in Diabetes

At the core of this fall's debate over Iraq lies one simple question: Can an increased number of U.S. troops subdue the Iraqi insurgency?

Ben Jones, Andreas Artemiou, Bing Li.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1--23.

Abstract:
We give a probabilistic analysis of a phenomenon in statistics which, until recently, has not received a convincing explanation. This phenomenon is that the leading principal components tend to possess more predictive power for a response variable than lower-ranking ones despite the procedure being unsupervised. Our result, in its most general form, shows that the phenomenon goes far beyond the context of linear regression and classical principal components — if an arbitrary distribution for the predictor $X$ and an arbitrary conditional distribution for $Yvert X$ are chosen then any measureable function $g(Y)$, subject to a mild condition, tends to be more correlated with the higher-ranking kernel principal components than with the lower-ranking ones. The “arbitrariness” is formulated in terms of unitary invariance then the tendency is explicitly quantified by exploring how unitary invariance relates to the Cauchy distribution. The most general results, for technical reasons, are shown for the case where the kernel space is finite dimensional. The occurency of this tendency in real world databases is also investigated to show that our results are consistent with observation.

Principal component analysis (PCA) is a well-established tool in machine learning and data processing. The principal axes in PCA were shown to be equivalent to the maximum marginal likelihood estimator of the factor loading matrix in a latent factor model for the observed data, assuming that the latent factors are independently distributed as standard normal distributions. However, the independence assumption may be unrealistic for many scenarios such as modeling multiple time series, spatial processes, and functional data, where the outcomes are correlated. In this paper, we introduce the generalized probabilistic principal component analysis (GPPCA) to study the latent factor model for multiple correlated outcomes, where each factor is modeled by a Gaussian process. Our method generalizes the previous probabilistic formulation of PCA (PPCA) by providing the closed-form maximum marginal likelihood estimator of the factor loadings and other parameters. Based on the explicit expression of the precision matrix in the marginal likelihood that we derived, the number of the computational operations is linear to the number of output variables. Furthermore, we also provide the closed-form expression of the marginal likelihood when other covariates are included in the mean structure. We highlight the advantage of GPPCA in terms of the practical relevance, estimation accuracy and computational convenience. Numerical studies of simulated and real data confirm the excellent finite-sample performance of the proposed approach.

Feature screening is a powerful tool in processing high-dimensional data. When the sample size N and the number of features p are both large, the implementation of classic screening methods can be numerically challenging. In this paper, we propose a distributed screening framework for big data setup. In the spirit of 'divide-and-conquer', the proposed framework expresses a correlation measure as a function of several component parameters, each of which can be distributively estimated using a natural U-statistic from data segments. With the component estimates aggregated, we obtain a final correlation estimate that can be readily used for screening features. This framework enables distributed storage and parallel computing and thus is computationally attractive. Due to the unbiased distributive estimation of the component parameters, the final aggregated estimate achieves a high accuracy that is insensitive to the number of data segments m. Under mild conditions, we show that the aggregated correlation estimator is as efficient as the centralized estimator in terms of the probability convergence bound and the mean squared error rate; the corresponding screening procedure enjoys sure screening property for a wide range of correlation measures. The promising performances of the new method are supported by extensive numerical examples.

This work is concerned with the non-negative rank-1 robust principal component analysis (RPCA), where the goal is to recover the dominant non-negative principal components of a data matrix precisely, where a number of measurements could be grossly corrupted with sparse and arbitrary large noise. Most of the known techniques for solving the RPCA rely on convex relaxation methods by lifting the problem to a higher dimension, which significantly increase the number of variables. As an alternative, the well-known Burer-Monteiro approach can be used to cast the RPCA as a non-convex and non-smooth $ell_1$ optimization problem with a significantly smaller number of variables. In this work, we show that the low-dimensional formulation of the symmetric and asymmetric positive rank-1 RPCA based on the Burer-Monteiro approach has benign landscape, i.e., 1) it does not have any spurious local solution, 2) has a unique global solution, and 3) its unique global solution coincides with the true components. An implication of this result is that simple local search algorithms are guaranteed to achieve a zero global optimality gap when directly applied to the low-dimensional formulation. Furthermore, we provide strong deterministic and probabilistic guarantees for the exact recovery of the true principal components. In particular, it is shown that a constant fraction of the measurements could be grossly corrupted and yet they would not create any spurious local solution.

Raj Kamal Maurya, Yogesh Mani Tripathi.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 2, 345--369.

Abstract:
We consider estimation of the multicomponent stress-strength reliability under progressive Type II censoring under the assumption that stress and strength variables follow Burr XII distributions with a common shape parameter. Maximum likelihood estimates of the reliability are obtained along with asymptotic intervals when common shape parameter may be known or unknown. Bayes estimates are also derived under the squared error loss function using different approximation methods. Further, we obtain exact Bayes and uniformly minimum variance unbiased estimates of the reliability for the case common shape parameter is known. The highest posterior density intervals are also obtained. We perform Monte Carlo simulations to compare the performance of proposed estimates and present a discussion based on this study. Finally, two real data sets are analyzed for illustration purposes.

Abedin Haidari, Amir T. Payandeh Najafabadi, Narayanaswamy Balakrishnan.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 1, 150--166.

Abstract:
Consider two parallel systems, say $A$ and $B$, with respective lifetimes $T_{1}$ and $T_{2}$ wherein independent component lifetimes of each system follow exponentiated generalized gamma distribution with possibly different exponential shape and scale parameters. We show here that $T_{2}$ is smaller than $T_{1}$ with respect to the usual stochastic order (reversed hazard rate order) if the vector of logarithm (the main vector) of scale parameters of System $B$ is weakly weighted majorized by that of System $A$, and if the vector of exponential shape parameters of System $A$ is unordered mojorized by that of System $B$. By means of some examples, we show that the above results can not be extended to the hazard rate and likelihood ratio orders. However, when the scale parameters of each system divide into two homogeneous groups, we verify that the usual stochastic and reversed hazard rate orders can be extended, respectively, to the hazard rate and likelihood ratio orders. The established results complete and strengthen some of the known results in the literature.

Vladimir Koltchinskii, Matthias Löffler, Richard Nickl.

Source: The Annals of Statistics, Volume 48, Number 1, 464--490.

Abstract:
We study principal component analysis (PCA) for mean zero i.i.d. Gaussian observations $X_{1},dots,X_{n}$ in a separable Hilbert space $mathbb{H}$ with unknown covariance operator $Sigma $. The complexity of the problem is characterized by its effective rank $mathbf{r}(Sigma):=frac{operatorname{tr}(Sigma)}{|Sigma |}$, where $mathrm{tr}(Sigma)$ denotes the trace of $Sigma $ and $|Sigma|$ denotes its operator norm. We develop a method of bias reduction in the problem of estimation of linear functionals of eigenvectors of $Sigma $. Under the assumption that $mathbf{r}(Sigma)=o(n)$, we establish the asymptotic normality and asymptotic properties of the risk of the resulting estimators and prove matching minimax lower bounds, showing their semiparametric optimality.

Davy Paindaveine, Julien Remy, Thomas Verdebout.

Source: The Annals of Statistics, Volume 48, Number 1, 324--345.

Abstract:
We consider the problem of testing, on the basis of a $p$-variate Gaussian random sample, the null hypothesis $mathcal{H}_{0}:oldsymbol{ heta}_{1}=oldsymbol{ heta}_{1}^{0}$ against the alternative $mathcal{H}_{1}:oldsymbol{ heta}_{1} eq oldsymbol{ heta}_{1}^{0}$, where $oldsymbol{ heta}_{1}$ is the “first” eigenvector of the underlying covariance matrix and $oldsymbol{ heta}_{1}^{0}$ is a fixed unit $p$-vector. In the classical setup where eigenvalues $lambda_{1}>lambda_{2}geq cdots geq lambda_{p}$ are fixed, the Anderson ( Ann. Math. Stat. 34 (1963) 122–148) likelihood ratio test (LRT) and the Hallin, Paindaveine and Verdebout ( Ann. Statist. 38 (2010) 3245–3299) Le Cam optimal test for this problem are asymptotically equivalent under the null hypothesis, hence also under sequences of contiguous alternatives. We show that this equivalence does not survive asymptotic scenarios where $lambda_{n1}/lambda_{n2}=1+O(r_{n})$ with $r_{n}=O(1/sqrt{n})$. For such scenarios, the Le Cam optimal test still asymptotically meets the nominal level constraint, whereas the LRT severely overrejects the null hypothesis. Consequently, the former test should be favored over the latter one whenever the two largest sample eigenvalues are close to each other. By relying on the Le Cam’s asymptotic theory of statistical experiments, we study the non-null and optimality properties of the Le Cam optimal test in the aforementioned asymptotic scenarios and show that the null robustness of this test is not obtained at the expense of power. Our asymptotic investigation is extensive in the sense that it allows $r_{n}$ to converge to zero at an arbitrary rate. While we restrict to single-spiked spectra of the form $lambda_{n1}>lambda_{n2}=cdots =lambda_{np}$ to make our results as striking as possible, we extend our results to the more general elliptical case. Finally, we present an illustrative real data example.

Zhou Fan, Iain M. Johnstone.

Source: The Annals of Statistics, Volume 47, Number 5, 2855--2886.

Abstract:
We study the spectra of MANOVA estimators for variance component covariance matrices in multivariate random effects models. When the dimensionality of the observations is large and comparable to the number of realizations of each random effect, we show that the empirical spectra of such estimators are well approximated by deterministic laws. The Stieltjes transforms of these laws are characterized by systems of fixed-point equations, which are numerically solvable by a simple iterative procedure. Our proof uses operator-valued free probability theory, and we establish a general asymptotic freeness result for families of rectangular orthogonally invariant random matrices, which is of independent interest. Our work is motivated in part by the estimation of components of covariance between multiple phenotypic traits in quantitative genetics, and we specialize our results to common experimental designs that arise in this application.

Breaking down into interchangeable pieces. For many years, software innovators have been trying to make software more like computer hardware, which is assembled from cheap, mass-produced components that connect together using standard interfaces. Component-based development (CBD) uses this approach to assemble software from reusable components within frameworks such as CORBA, Sun's Enterprise Java Beans (EJBs) and Microsoft COM. Today's service oriented architectures, based on web services, go a step further by encapsulating components in a standards-based service interface, which allows components to be reused outside their native framework. Componentization is not limited to software; through the use of subcontracting and outsourcing, it can also apply to business organizations and processes.

Zhonghua Liu, Ian Barnett, Xihong Lin.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 433--451.

Abstract:
Principal component analysis (PCA) is a popular method for dimension reduction in unsupervised multivariate analysis. However, existing ad hoc uses of PCA in both multivariate regression (multiple outcomes) and multiple regression (multiple predictors) lack theoretical justification. The differences in the statistical properties of PCAs in these two regression settings are not well understood. In this paper we provide theoretical results on the power of PCA in genetic association testings in both multiple phenotype and SNP-set settings. The multiple phenotype setting refers to the case when one is interested in studying the association between a single SNP and multiple phenotypes as outcomes. The SNP-set setting refers to the case when one is interested in studying the association between multiple SNPs in a SNP set and a single phenotype as the outcome. We demonstrate analytically that the properties of the PC-based analysis in these two regression settings are substantially different. We show that the lower order PCs, that is, PCs with large eigenvalues, are generally preferred and lead to a higher power in the SNP-set setting, while the higher-order PCs, that is, PCs with small eigenvalues, are generally preferred in the multiple phenotype setting. We also investigate the power of three other popular statistical methods, the Wald test, the variance component test and the minimum $p$-value test, in both multiple phenotype and SNP-set settings. We use theoretical power, simulation studies, and two real data analyses to validate our findings.

Jason M. Klusowski, Yihong Wu.

Source: Bernoulli, Volume 26, Number 3, 1635--1664.

Abstract:
Learning properties of large graphs from samples has been an important problem in statistical network analysis since the early work of Goodman ( Ann. Math. Stat. 20 (1949) 572–579) and Frank ( Scand. J. Stat. 5 (1978) 177–188). We revisit a problem formulated by Frank ( Scand. J. Stat. 5 (1978) 177–188) of estimating the number of connected components in a large graph based on the subgraph sampling model, in which we randomly sample a subset of the vertices and observe the induced subgraph. The key question is whether accurate estimation is achievable in the sublinear regime where only a vanishing fraction of the vertices are sampled. We show that it is impossible if the parent graph is allowed to contain high-degree vertices or long induced cycles. For the class of chordal graphs, where induced cycles of length four or above are forbidden, we characterize the optimal sample complexity within constant factors and construct linear-time estimators that provably achieve these bounds. This significantly expands the scope of previous results which have focused on unbiased estimators and special classes of graphs such as forests or cliques. Both the construction and the analysis of the proposed methodology rely on combinatorial properties of chordal graphs and identities of induced subgraph counts. They, in turn, also play a key role in proving minimax lower bounds based on construction of random instances of graphs with matching structures of small subgraphs.

Ruosi Guo, Chunming Zhang, Zhengjun Zhang.

Source: Statistical Science, Volume 35, Number 1, 145--157.

Abstract:
In many scientific disciplines, finding hidden influential factors behind observational data is essential but challenging. The majority of existing approaches, such as the independent component analysis (${mathrm{ICA}}$), rely on linear transformation, that is, true signals are linear combinations of hidden components. Motivated from analyzing nonlinear temporal signals in neuroscience, genetics, and finance, this paper proposes the “maximum independent component analysis” (${mathrm{MaxICA}}$), based on max-linear combinations of components. In contrast to existing methods, ${mathrm{MaxICA}}$ benefits from focusing on significant major components while filtering out ignorable components. A major tool for parameter learning of ${mathrm{MaxICA}}$ is an augmented genetic algorithm, consisting of three schemes for the elite weighted sum selection, randomly combined crossover, and dynamic mutation. Extensive empirical evaluations demonstrate the effectiveness of ${mathrm{MaxICA}}$ in either extracting max-linearly combined essential sources in many applications or supplying a better approximation for nonlinearly combined source signals, such as $mathrm{EEG}$ recordings analyzed in this paper.

M Steriade
Aug 1, 1993; 13:3252-3265
Articles

The post SOLIDWORKS Electrical Formula SAE Tutorial: How to open a SOLIDWORKS Electrical project and associate electrical components appeared first on SOLIDWORKS Education Blog.

Hi, I’m Mike Dady, Application Engineer for Alignex. As many of you probably know, the Toolbox Add-In is a database that allows for the quick addition of fasteners and other hardware to a SOLIDWORKS Assembly. However, many don’t realize that

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The post How to Create a Custom Toolbox Component appeared first on SOLIDWORKS Tech Blog.

Everyone knows SOLIDWORKS is very flexible and user friendly to execute the commands to complete any 3D design easily. When it comes to handling Complex assemblies (Increased in number of components) many of us will search for special tools to

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The post SOLIDWORKS Quick tips – Advanced Component Selection appeared first on SOLIDWORKS Tech Blog.

The post Lighten your Components by over 50 Percent with Topology Optimization in SOLIDWORKS Simulation appeared first on The SOLIDWORKS Blog.

Several studies have focused on birth weight heritability, reporting results that range between 40% and 80%. Few studies have focused on the process of weight gain and were mainly based on heterogeneous samples of infants.

The present work looks at a uniform set of healthy preterm newborn twins. The resulting high heritability estimate could suggest using the inclusion criteria to identify genes that regulate postnatal weight gain or failure. (Read the full article)

Clinic-based weight control treatments for youth have largely been designed for preadolescent children and their families by using family-based care, a strategy that may be less appealing to adolescents as they become increasingly motivated by peer acceptance rather than parental influence.

To our knowledge, this is the first study to demonstrate the efficacy of a primary care–based, multicomponent lifestyle intervention specifically tailored for overweight adolescent females and demonstrating a sustained effect (at 12 months) extending beyond the active 5-month intervention. (Read the full article)

The Cpx stress response is widespread among Enterobacteriaceae. We have previously reported a mutation in cpxA in a multidrug resistant strain of Klebsiella aerogenes isolated from a patient treated with imipenem. This mutation yields to a single amino acid substitution (Y144N) located in the periplasmic sensor domain of CpxA. In this work, we sought to characterize this mutation in Escherichia coli by using genetic and biochemical approaches. Here, we show that cpxA^Y144N is an activated allele that confers resistance to β-lactams and aminoglycosides in a CpxR-dependent manner, by regulating the expression of the OmpF porin and the AcrD efflux pump, respectively. We also demonstrate the intimate interconnection between Cpx system and peptidoglycan integrity on the expression of an exogenous AmpC β-lactamase by using imipenem as a cell wall active antibiotic or inactivation of penicillin-binding proteins. Moreover, our data indicate that the Y144N substitution abrogates the interaction between CpxA and CpxP and increase phosphotransfer activity on CpxR. Because the addition of a strong AmpC inducer such as imipenem is known to causes abnormal accumulation of muropeptides (disaccharide-pentapeptide, N-acetylglucosamyl-1,6-anhydro-N-acetylmuramyl-l-alanyl-d-glutamy-meso-diaminopimelic-acid-d-alanyl-d-alanine) in the periplasmic space, we propose these molecules activate the Cpx system by displacing CpxP from the sensor domain of CpxA. Altogether, these data could explain why large perturbations to peptidoglycan caused by imipenem lead to mutational activation of the Cpx system and bacterial adaptation through multidrug resistance. These results also validate the Cpx system, in particular the interaction between CpxA and CpxP, as a promising therapeutic target.

A 64-core/128-thread CPU. A new challenger in laptop processors. A feisty new fighter in midrange graphics. These three things have three letters in common. Plus: SSDs take on stunning new capacities, speeds, and looks.

While few auto component manufacturers in the green zone are planning to restart operations, others operating in orange zones are seeking permission to resume their work again. Needless to say, those...

Hi, I want to add values to components in my SiP design such as 1nF or 15nH. There is already in existence a COMP_VALUE property reserved for this as shown during BOM generation. This property is not visible under the Edit/Properties dialog for component or symbol find filters. We have already created user properties called COMP_MFG and COMP_MFG_PN that it editable at a component level. When we try to add COMP_VALUE it is reported as a reserved name in Cadence but this name is not listed in the properties dialog. Is there a way to turn on the visibility and editablility of this or other hidden reserved Cadence property names? How can I assign a string value to the COMP_VALUE property?

Thanks

We’ve all seen bar codes and the more modern QR codes. They’re everywhere you go – items at the grocery store, advertisements and posters, even on websites. Did you know that, with the productivity toolbox in Allegro Package Designe...(read more)

I would like to add these components to the component bank in ORCAD simulation. Even an accessible or free course that explained how to create these components.

The ByteComponentRaster.verify() method in Oracle Java versions prior to 7u25 is vulnerable to a memory corruption vulnerability that allows bypassing of "dataOffsets[]" boundary checks. This exploit code demonstrates remote code execution by popping calc.exe. It was obtained through the Packet Storm Bug Bounty program.

The ByteComponentRaster.verify() method in Oracle Java versions prior to 7u25 is vulnerable to a memory corruption vulnerability that allows bypassing of "dataOffsets[]" boundary checks. This vulnerability allows for remote code execution. User interaction is required for this exploit in that the target must visit a malicious page or open a malicious file. This finding was purchased through the Packet Storm Bug Bounty program.

The ShortComponentRaster.verify() method in Oracle Java versions prior to 7u25 is vulnerable to a memory corruption vulnerability that allows bypassing of "dataOffsets[]" boundary checks when the "numDataElements" field is 0. This exploit code demonstrates remote code execution by popping calc.exe. It was obtained through the Packet Storm Bug Bounty program.

The ShortComponentRaster.verify() method in Oracle Java versions prior to 7u25 is vulnerable to a memory corruption vulnerability that allows bypassing of "dataOffsets[]" boundary checks when the "numDataElements" field is 0. This vulnerability allows for remote code execution. User interaction is required for this exploit in that the target must visit a malicious page or open a malicious file. This finding was purchased through the Packet Storm Bug Bounty program.