Bitvector filtering is an important query processing technique that can significantly reduce the cost of execution, especially for complex decision support queries with multiple joins. Despite its wide application, however, its implication to query optimization is not well understood.

In this work, we study how bitvector filters impact query optimization. We show that incorporating bitvector filters into query optimization straightforwardly can increase the plan space complexity by an exponential factor in the number of relations in the query. We analyze the plans with bitvector filters for star and snowflake queries in the plan space of right deep trees without cross products. Surprisingly, with some simplifying assumptions, we prove that, the plan of the minimal cost with bitvector filters can be found from a linear number of plans in the number of relations in the query. This greatly reduces the plan space complexity for such queries from exponential to linear.

Motivated by our analysis, we propose an algorithm that accounts for the impact of bitvector filters in query optimization. Our algorithm optimizes the join order for an arbitrary decision support query by choosing from a linear number of candidate plans in the number of relations in the query. We implement our algorithm in Microsoft SQL Server as a transformation rule. Our evaluation on both industry standard benchmarks and customer workload shows that, compared with the original Microsoft SQL Server, our technique reduces the total CPU execution time by 22%-64% for the workloads, with up to two orders of magnitude reduction in CPU execution time for individual queries.

We develop a categorical compositional distributional semantics for Lambek Calculus with a Relevant Modality !L*, which has a limited edition of the contraction and permutation rules. The categorical part of the semantics is a monoidal biclosed category with a coalgebra modality, very similar to the structure of a Differential Category. We instantiate this category to finite dimensional vector spaces and linear maps via "quantisation" functors and work with three concrete interpretations of the coalgebra modality. We apply the model to construct categorical and concrete semantic interpretations for the motivating example of !L*: the derivation of a phrase with a parasitic gap. The effectiveness of the concrete interpretations are evaluated via a disambiguation task, on an extension of a sentence disambiguation dataset to parasitic gap phrase one, using BERT, Word2Vec, and FastText vectors and Relational tensors.

A system and method that facilitates urban traffic state detection based on support vector machine (SVM) and multilayer perceptron (MLP) classifiers is provided. Moreover, the SVM and MLP classifiers are fused into a cascaded two-tier classifier that improves the accuracy of the traffic state classification. To further improve the accuracy, the cascaded two-tier classifier (e.g., MLP-SVM), a single SVM classifier and a single MLP classifier are fused to determine a final decision for a traffic state. In addition, fusion strategies are employed during training and implementation phases to compensate for data acquisition and classification errors caused by noise and/or outliers.

A vector data access unit includes data access ordering circuitry, for issuing data access requests indicated by elements of earlier and a later vector instructions, one being a write instruction. An element indicating the next data access for each of the instructions is determined. The next data accesses for the earlier and the later instructions may be reordered. The next data access of the earlier instruction is selected if the position of the earlier instruction's next data element is less than or equal to the position of the later instruction's next data element minus a predetermined value. The next data access of the later instruction may be selected if the position of the earlier instruction's next data element is higher than the position of the later instruction's next data element minus a predetermined value. Thus data accesses from earlier and later instructions are partially interleaved.

Identification of maximum power scatters in an N-dimensional dataset generally requires two basic steps. The first step is to identify the max power scatters of the dataset and the second step removes neighboring power scatters (e.g., “hits”) of lower power. Current naïve approaches utilize an inefficient and computationally intensive brute force implementation which requires multiple comparisons of each initial “hit” power to all “hits” of lesser power. Such brute force implementations require 2×N×(M−1)! comparisons, where N is the number of dimensions and M is the number of “hits.” Embodiments of the present disclosure utilize vectorization to identify a plurality of neighboring hits for each max power scatter and removes the neighboring hits of lesser power that are within a predetermined isolation region. Advantageously, embodiments of the present invention perform M−1 comparisons.

According to one embodiment, a first gene encodes a reporter protein. The first gene is disposed at the downstream of the gene promoter. A second gene is disposed at the downstream of the gene promoter and encodes a replication origin-binding protein. An internal ribosome entry site is disposed between the first gene and the second gene. The transcription termination signal sequence encodes a signal for terminating the transcription of the first gene and the second gene. A replication origin sequence is recognized by the replication origin-binding protein.

One embodiment relates to a feedback receiver (FBR). The FBR includes a FBR signal input configured to receive a radio frequency (RF) signal, a first local oscillator (LO) signal input configured to receive a first LO signal having an LO frequency, and a second LO signal input configured to receive a second LO signal having the LO frequency. The second LO signal is phase shifted by approximately 90° relative to the first LO signal. FBR also includes a divider that induces a time-varying phase shift in the first and second LO signals while concurrently retaining a 90° phase shift between the first and second LO signals.

The present disclosure relates to a method and apparatus for encoding/decoding a motion vector and a method and apparatus for encoding/decoding video using same. The motion vector encoding method includes selecting a predicted motion vector candidate set including one or more predicted motion vector candidates for a block; determining one or more search ranges for predicted motion vector candidate set; selecting one predicted motion vector candidate among one or more predicted motion vector candidates as predicted motion vector for each search point with respect to each search point within search range by first determination criterion prearranged with video decoding apparatus; selecting one predicted motion vector among the predicted motion vectors for each search point by a second determination criterion not prearranged with the video decoding apparatus, and determining predicted motion vector, differential motion vector, and current motion vector; and generating and encoding the differential motion vector as motion information.

A video decoding method using an inter prediction, includes: reconstructing a first differential motion vector and a second differential motion vector of a current block by decoding encoded data; deriving a first predicted motion vector and a second predicted motion vector of the current block from one or more neighboring blocks of the current block; generating a first motion vector of the current block by adding the first candidate motion vector to the first differential motion vector, and a second motion vector of the current block by adding the second candidate motion vector to the second differential motion vector; generating a predicted block of the current block by using the first and second motion vectors; reconstructing a residual block by decoding residual signals included in the encoded data; and adding each pixel value of the predicted block to a corresponding pixel value of the residual block.

A video decoding method using an inter prediction, includes: reconstructing a first differential motion vector and a second differential motion vector of a current block by decoding encoded data; deriving a first predicted motion vector and a second predicted motion vector of the current block from one or more neighboring blocks of the current block; generating a first motion vector of the current block by adding the first candidate motion vector to the first differential motion vector, and a second motion vector of the current block by adding the second candidate motion vector to the second differential motion vector; generating a predicted block of the current block by using the first and second motion vectors; reconstructing a residual block by decoding residual signals included in the encoded data; and adding each pixel value of the predicted block to a corresponding pixel value of the residual block.

In various embodiments, a spectral graph partitioner (“SP”) of a graph partitioning system (“GPS”) may partition a data flow graph associated with a program into a plurality of subgraphs to be used to perform analysis or debugging. The SP may generate estimated eigenvectors for a matrix representing the graph through minimization of a function on the vectors. The SP may generate multiple eigenvectors to perform the clustering in a multi-dimensional space described by the eigenvectors. The SP may refine the clustering by repeating generation of eigenvectors to describe higher-dimensional spaces and perform further clustering. The SP may also determine quality metrics for the clusters and may stop refinement based on the quality metrics. The GPS may select between utilizing the SP or utilizing one or more other partitioners based on various factors such as, for example, graph size or quality metrics. Other embodiments may be described and/or claimed.

The present invention relates to a thermal vector system for solar concentration plants, in particular for parabolic trough solar concentration plants, both for industrial and domestic use, comprising a solid state thermal vector. A preferred solar concentration plant comprises one or more solar collectors (1), an heat exchanger (3-5), a heat accumulator (2) and a connecting pipe circuit, in which a solid state thermal vector is pushed through said circuit by mechanical means (6).

Examples of the present disclosure provide apparatuses and methods for performing shift operations in a memory. An example method comprises performing a shift operation a first element stored in a first group of memory cells coupled to a first access line and a number of sense lines of a memory array and a second element stored in a second group of memory cells coupled to a second access line and the number of sense lines of the memory array. The method can include shifting the first element by a number of bit positions defined by the second element by performing a number of AND operations, OR operations, SHIFT operations, and INVERT operations performed without transferring data via an input/output (I/O) line.

A first wireless device may determine a bandwidth for transmitting a frame, calculate two or more Spatial Reuse (SR) parameter values for the bandwidth, set, using the SR parameter values, first and second SR fields of the frame based on the bandwidth and a channel center frequency in which the bandwidth is carried, and transmit the frame to a second wireless device on the bandwidth. The first and second SR fields may be set to a first value when the bandwidth is a 40 MHz bandwidth and the channel center frequency is in a 2.4 GHz band. The first and second SR fields may be set to the first value when the bandwidth is an 80+80 MHz bandwidth and the channel center frequency is in a 5 GHz band. The first value may be a minimum of SR parameter values for first and second bandwidths in the bandwidth.

The invention relates to an encoder and a decoder and methods therein for supporting split gain shape vector encoding and decoding. The method performed by an encoder, where the encoding of each vector segment is subjected to a constraint related to a maximum number of bits, BMAX, allowed for encoding a vector segment. The method comprises, determining an initial number, Np—init, of segments for a target vector x; and further determining an average number of bits per segment, BAVG, based on a vector bit budget and Np—init. The method further comprises determining a final number of segments to be used, for the vector x, in the gain shape vector encoding, based on energies of the Np—init segments and a difference between BMAX and BAVG. The performing of the method enables an efficient allocation of the bits of the bit budget over the target vector.

An electronic arrangement and method for providing a signal characterized by reduced phase noise having a signal source for providing a stimulus signal, a modulator coupled to the signal source for generating a modulated signal as function of the stimulus signal and a local oscillator signal, and a mixer combining the stimulus and modulated signals to generate a mixed signal that includes a component characterized by a mathematical difference of the stimulus signal and the modulated signal. The modulated signal is substantially identical to the stimulus signal and offset by a frequency of the local oscillator signal, so that the difference component of the mixed signal results in a local oscillator signal wherein the stimulus signal phase noise generated by the signal source has been mathematically cancelled.

A vector network analyzer (VNA) for analyzing the response of a device under test (DUT), the VNA comprising a plurality of VNA ports configured to be connected to the DUT; a plurality of source ports configured to be connected to the VNA ports; a plurality of couplers for coupling a plurality of coupled signals, wherein said plurality of coupled signals are combined to provide a sum signal; and a receiver configured to receive said forward sum signal.

Sometimes you need to experiment to grow as an artist. What better place to try out new design ideas than the Drawing Vector Graphics Laboratory? Every Wednesday, Von Glitschka introduces a new method, tool, or resource to stretch your creative muscle and explore a new artistic style. Each lesson pulls back the curtain on Von's design process—the good, the bad, and the ugly—to give beginners the self-confidence they need to start drawing and provide experts an inside look at a fellow professional's workflow.

Note: Because this is an ongoing series, viewers will not receive a certificate of completion.

#architektura #architekt #dom #design

Yuji Nakatsukasa
Math. Comp. 89 (2020), 1843-1866.
Abstract, references and article information

T. Bodnar, S. Mazur, S. Muhinyuza and N. Parolya
Theor. Probability and Math. Statist. 99 (2020), 39-52.
Abstract, references and article information

Maddalena Cavicchioli.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 605--631.

Abstract:
The paper treats the modeling of stationary multivariate stochastic processes via a frequency domain model expressed in terms of cepstrum theory. The proposed model nests the vector exponential model of [20] as a special case, and extends the generalised cepstral model of [36] to the multivariate setting, answering a question raised by the last authors in their paper. Contemporarily, we extend the notion of generalised autocovariance function of [35] to vector time series. Then we derive explicit matrix formulas connecting generalised cepstral and autocovariance matrices of the process, and prove the consistency and asymptotic properties of the Whittle likelihood estimators of model parameters. Asymptotic theory for the special case of the vector exponential model is a significant addition to the paper of [20]. We also provide a mathematical machinery, based on matrix differentiation, and computational methods to derive our results, which differ significantly from those employed in the univariate case. The utility of the proposed model is illustrated through Monte Carlo simulation from a bivariate process characterized by a high dynamic range, and an empirical application on time varying minimum variance hedge ratios through the second moments of future and spot prices in the corn commodity market.

Xuening Zhu.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1413--1448.

Abstract:
High dimensional time series receive considerable attention recently, whose temporal and cross-sectional dependency could be captured by the vector autoregression (VAR) model. To tackle with the high dimensionality, penalization methods are widely employed. However, theoretically, the existing studies of the penalization methods mainly focus on $i.i.d$ data, therefore cannot quantify the effect of the dependence level on the convergence rate. In this work, we use the spectral properties of the time series to quantify the dependence and derive a nonasymptotic upper bound for the estimation errors. By focusing on the nonconcave penalization methods, we manage to establish the oracle properties of the penalized VAR model estimation by considering the effects of temporal and cross-sectional dependence. Extensive numerical studies are conducted to compare the finite sample performance using different penalization functions. Lastly, an air pollution data of mainland China is analyzed for illustration purpose.

In this paper, we extend the methodology developed for Support Vector Machines (SVM) using the $ell_2$-norm ($ell_2$-SVM) to the more general case of $ell_p$-norms with $p>1$ ($ell_p$-SVM). We derive second order cone formulations for the resulting dual and primal problems. The concept of kernel function, widely applied in $ell_2$-SVM, is extended to the more general case of $ell_p$-norms with $p>1$ by defining a new operator called multidimensional kernel. This object gives rise to reformulations of dual problems, in a transformed space of the original data, where the dependence on the original data always appear as homogeneous polynomials. We adapt known solution algorithms to efficiently solve the primal and dual resulting problems and some computational experiments on real-world datasets are presented showing rather good behavior in terms of the accuracy of $ell_p$-SVM with $p>1$.

Daniela Bertacchi, Fabio Zucca.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 2, 426--438.

Abstract:
Given a branching random walk on a set $X$, we study its extinction probability vectors $mathbf{q}(cdot,A)$. Their components are the probability that the process goes extinct in a fixed $Asubseteq X$, when starting from a vertex $xin X$. The set of extinction probability vectors (obtained letting $A$ vary among all subsets of $X$) is a subset of the set of the fixed points of the generating function of the branching random walk. In particular here we are interested in the cardinality of the set of extinction probability vectors. We prove results which allow to understand whether the probability of extinction in a set $A$ is different from the one of extinction in another set $B$. In many cases there are only two possible extinction probability vectors and so far, in more complicated examples, only a finite number of distinct extinction probability vectors had been explicitly found. Whether a branching random walk could have an infinite number of distinct extinction probability vectors was not known. We apply our results to construct examples of branching random walks with uncountably many distinct extinction probability vectors.

Arctic sea ice extent (SIE) in September 2019 ranked second-to-lowest in history and is trending downward. The understanding of how internal variability amplifies the effects of external $ ext{CO}_2$ forcing is still limited. We propose the VARCTIC, which is a Vector Autoregression (VAR) designed to capture and extrapolate Arctic feedback loops. VARs are dynamic simultaneous systems of equations, routinely estimated to predict and understand the interactions of multiple macroeconomic time series. Hence, the VARCTIC is a parsimonious compromise between fullblown climate models and purely statistical approaches that usually offer little explanation of the underlying mechanism. Our "business as usual" completely unconditional forecast has SIE hitting 0 in September by the 2060s. Impulse response functions reveal that anthropogenic $ ext{CO}_2$ emission shocks have a permanent effect on SIE - a property shared by no other shock. Further, we find Albedo- and Thickness-based feedbacks to be the main amplification channels through which $ ext{CO}_2$ anomalies impact SIE in the short/medium run. Conditional forecast analyses reveal that the future path of SIE crucially depends on the evolution of $ ext{CO}_2$ emissions, with outcomes ranging from recovering SIE to it reaching 0 in the 2050s. Finally, Albedo and Thickness feedbacks are shown to play an important role in accelerating the speed at which predicted SIE is heading towards 0.

In the variational relevance vector machine, the gamma distribution is representative as a hyperprior over the noise precision of automatic relevance determination prior. Instead of the gamma hyperprior, we propose to use the inverse gamma hyperprior with a shape parameter close to zero and a scale parameter not necessary close to zero. This hyperprior is associated with the concept of a weakly informative prior. The effect of this hyperprior is investigated through regression to non-homogeneous data. Because it is difficult to capture the structure of such data with a single kernel function, we apply the multiple kernel method, in which multiple kernel functions with different widths are arranged for input data. We confirm that the degrees of freedom in a model is controlled by adjusting the scale parameter and keeping the shape parameter close to zero. A candidate for selecting the scale parameter is the predictive information criterion. However the estimated model using this criterion seems to cause over-fitting. This is because the multiple kernel method makes the model a situation where the dimension of the model is larger than the data size. To select an appropriate scale parameter even in such a situation, we also propose an extended prediction information criterion. It is confirmed that a multiple kernel relevance vector regression model with good predictive accuracy can be obtained by selecting the scale parameter minimizing extended prediction information criterion.

Taras Bodnar, Holger Dette, Nestor Parolya.

Source: The Annals of Statistics, Volume 47, Number 5, 2977--3008.

Abstract:
In this paper, new tests for the independence of two high-dimensional vectors are investigated. We consider the case where the dimension of the vectors increases with the sample size and propose multivariate analysis of variance-type statistics for the hypothesis of a block diagonal covariance matrix. The asymptotic properties of the new test statistics are investigated under the null hypothesis and the alternative hypothesis using random matrix theory. For this purpose, we study the weak convergence of linear spectral statistics of central and (conditionally) noncentral Fisher matrices. In particular, a central limit theorem for linear spectral statistics of large dimensional (conditionally) noncentral Fisher matrices is derived which is then used to analyse the power of the tests under the alternative. The theoretical results are illustrated by means of a simulation study where we also compare the new tests with several alternative, in particular with the commonly used corrected likelihood ratio test. It is demonstrated that the latter test does not keep its nominal level, if the dimension of one sub-vector is relatively small compared to the dimension of the other sub-vector. On the other hand, the tests proposed in this paper provide a reasonable approximation of the nominal level in such situations. Moreover, we observe that one of the proposed tests is most powerful under a variety of correlation scenarios.

Björn Böttcher, Martin Keller-Ressel, René L. Schilling.

Source: The Annals of Statistics, Volume 47, Number 5, 2757--2789.

Abstract:
We introduce two new measures for the dependence of $nge2$ random variables: distance multivariance and total distance multivariance . Both measures are based on the weighted $L^{2}$-distance of quantities related to the characteristic functions of the underlying random variables. These extend distance covariance (introduced by Székely, Rizzo and Bakirov) from pairs of random variables to $n$-tuplets of random variables. We show that total distance multivariance can be used to detect the independence of $n$ random variables and has a simple finite-sample representation in terms of distance matrices of the sample points, where distance is measured by a continuous negative definite function. Under some mild moment conditions, this leads to a test for independence of multiple random vectors which is consistent against all alternatives.

Bacterial artificial chromosome (BAC) clones are rendered electrocompetent and transformed with the recombinant shuttle vector, pLD53SCAB/AB-box. Cointegrates are selected by growth on chloramphenicol and ampicillin to ensure recombination of the shuttle vector into the BAC.

Plasmid DNA is prepared from the recombinant shuttle vector pLD53.SCAB/A-B created by cloning of the A and B homology arms for two-step bacterial artificial chromosome (BAC) engineering. To confirm that the A-box and B-box arms have been successfully incorporated into pLD53.SCAB, the pattern of enzyme digestion of the modified plasmid is compared with that of the unmodified pLD53.SCAB. Once the shuttle vector is shown to carry the proper sequences, it is ready for transfer into the BAC host.

This protocol describes the preparation of the shuttle vector before its introduction into bacterial artificial chromosome (BAC) host cells for BAC two-step engineering. The homology arm sequences, prepared previously, are introduced by ligation into the digested shuttle vector DNA to provide sites for recombination within the BAC clone. Crude lysates of individual bacterial transformants serve as templates in polymerase chain reaction (PCR) analysis to confirm the presence of the homology arms in the recombinant shuttle vector.

In two-step bacterial artificial chromosome (BAC) engineering, a single plasmid is introduced into the BAC-carrying cell lines. The shuttle vector pLD53.SCAB (or pLD53.SCAEB) carries the recA gene and the R6K origin, which requires the protein to replicate. PIR2 cells, expressing , are typically used for the amplification of the vector and maintain about 15 copies/cell of the donor vector, which is relatively stable in this host.

I previously wrote about the advantages of adding horizontal and vertical reference lines to a graph. You can also add a diagonal reference line to a graph. The SGPLOT procedure in SAS supports two primary ways to add a diagonal reference line: The LINEPARM statement enables you to specify a [...]

The post Add diagonal reference lines to SAS graphs: The LINEPARM and VECTOR statements appeared first on The DO Loop.

Efficient delivery of antigenic cargo to trigger protective immune responses is critical to the success of vaccination. Genetically engineered microorganisms, including virus, bacteria, and protozoa, can be modified to carry and deliver heterologous antigens to the host immune system. The biological vectors can induce a broad range of immune responses and enhance heterologous antigen-specific immunological outcomes. The protozoan genus Eimeria is widespread in domestic animals, causing serious coccidiosis. Eimeria parasites with strong immunogenicity are potent coccidiosis vaccine candidates and offer a valuable model of live vaccines against infectious diseases in animals. Eimeria parasites can also function as a vaccine vector. Herein, we review recent advances in design and application of recombinant Eimeria as a vaccine vector, which has been a topic of ongoing research in our laboratory. By recapitulating the establishment of an Eimeria transfection platform and its application, it will help lay the foundation for the future development of effective parasite-based vaccine delivery vectors and beyond.

Human adenoviruses have many attractive features for gene therapy applications. However, the high prevalence of preexisting immunity against these viruses in general populations worldwide has greatly limited their clinical utility. In addition, the most commonly used human adenovirus, human adenovirus subgroup C serotype 5 (HAd5), when systemically administered, triggers systemic inflammation and toxicity, with the liver being the most severely affected organ. Here, we evaluated the utility and safety of a new low-seroprevalence gorilla adenovirus (GAd; GC46) as a gene transfer vector in mice. Biodistribution studies revealed that systemically administered GAd had a selective and robust lung endothelial cell (EC) tropism with minimal vector expression throughout many other organs and tissues. Administration of a high dose of GAd accomplished extensive transgene expression in the lung yet elicited no detectable inflammatory histopathology in this organ. Furthermore, GAd, unlike HAd5, did not exhibit hepatotropism or induce liver inflammatory toxicity in mice, demonstrating the exceptional safety profile of the vector vis-à-vis systemic utility. We further demonstrated that the GAd capsid fiber shared the flexibility of the HAd5 equivalent for permitting genetic modification; GAd with the pan-EC-targeting ligand myeloid cell-binding peptide (MBP) incorporated in the capsid displayed a reduced lung tropism and efficiently retargeted gene expression to vascular beds in other organs.

IMPORTANCE In the aggregate, our mouse studies suggest that GAd is a promising gene therapy vector that utilizes lung ECs as a source of therapeutic payload production and a highly desirable toxicity profile. Further genetic engineering of the GAd capsid holds the promise of in vivo vector tropism modification and targeting.

We have been exploring the use of the live attenuated Salmonella enterica serovar Typhi Ty21a vaccine strain as a versatile oral vaccine vector for the expression and delivery of multiple foreign antigens, including Shigella O-antigens. In this study, we separately cloned genes necessary for the biosynthesis of the Shigella flexneri serotype 2a and 3a O-antigens, which have been shown to provide broad cross-protection to multiple disease-predominant S. flexneri serotypes. The cloned S. flexneri 2a rfb operon, along with bgt and gtrII, contained on the SfII bacteriophage, was sufficient in Ty21a to express the heterologous S. flexneri 2a O-antigen containing the 3,4 antigenic determinants. Further, this rfb operon, along with gtrA, gtrB, and gtrX contained on the Sfx bacteriophage and oac contained on the Sf6 bacteriophage, was sufficient to express S. flexneri 3a O-antigen containing the 6, 7, and 8 antigenic determinants. Ty21a, with these plasmid-carried or chromosomally inserted genes, demonstrated simultaneous and stable expression of homologous S. Typhi O-antigen plus the heterologous S. flexneri O-antigen. Candidate Ty21a vaccine strains expressing heterologous S. flexneri 2a or 3a lipopolysaccharide (LPS) elicited significant serum antibody responses against both homologous S. Typhi and heterologous Shigella LPS and protected mice against virulent S. flexneri 2a or 3a challenges. These new S. flexneri 2a and 3a O-antigen-expressing Ty21a vaccine strains, together with our previously constructed Ty21a strains expressing Shigella sonnei or Shigella dysenteriae 1 O-antigens, have the potential to be used together for simultaneous protection against the predominant causes of shigellosis worldwide as well as against typhoid fever.

Nordic Nanovector has appointed Dr Lars Nieba as the interim Chief Executive Officer. He is currently the company’s Chief Technology Officer and replaces Eduardo Bravo who as of today has left Nordic to pursue other career opportunities.

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Scientists have discovered a new approach in which three different gene delivery vectors were injected intravenously and directly into the kidneys of mice.

Combining different two drugs with different properties into nanovesicles surrounded by antibodies can hugely improve their delivery and efficiency. .

Barker Library - TA350.V34 2016

Last year, VELOCITY WEAPON (US | UK)  took the sci-fi world by storm with its brilliant plot twists, widescreen space battles, and deep questions about AI and the future of humanity. It garnered a nomination for The Philip …

The post Cover Launch: CHAOS VECTOR by Megan E. O’Keefe appeared first on Orbit Books.