An Information-Theoretic Measure of Cultural Success

I develop a simple but principled method for measuring the amount of culturally-transmitted information from a written target work that is actually retained in human minds and capable of influencing behavior. Using procedures inspired by Claude Shannon’s 1951 method for estimating the entropy of written English, I estimate the entropy of samples from the target work with a treatment group (those that have read a target work) and a control group (those who are of the same culture but who have not read the target work), using human minds as encoders-decoders in the communication model. KL divergence quantifies the information that the treatment group already knows relative to the control group. This method controls for shared cultural inheritance and does not require commitments to what information from the target work is important. The general technique can be profitably extended to a variety of domains, including evolutionary theory, methods of teaching, and the study of music.

Dynamically corrected gates from geometric space curves

Quantum information technologies demand highly accurate control over quantum systems. Achieving this requires control techniques that perform well despite the presence of decohering noise and other adverse effects. Here, we review a general technique for designing control fields that dynamically correct errors while performing operations using a close relationship between quantum evolution and geometric space curves. This approach provides access to the global solution space of control fields that accomplish a given task, facilitating the design of experimentally feasible gate operations for a wide variety of applications.

LinearTurboFold: Linear-time global prediction of conserved structures for RNA homologs with applications to SARS-CoV-2

The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length and are thus infeasible for coronaviruses, which possess the longest genomes (∼30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single-sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurboFold’s purely in silico prediction not only is close to experimentally guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5′ and 3′ untranslated regions (UTRs) (∼29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies undiscovered conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, small interfering RNAs (siRNAs), CRISPR-Cas13 guide RNAs, and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies and will be a useful tool in fighting the current and future pandemics.

Security of quantum key distribution with intensity correlations

The decoy-state method in quantum key distribution (QKD) is a popular technique to approximately achieve the performance of ideal single-photon sources by means of simpler and practical laser sources. In high-speed decoy-state QKD systems, however, intensity correlations between succeeding pulses leak information about the users' intensity settings, thus invalidating a key assumption of this approach. Here, we solve this pressing problem by developing a general technique to incorporate arbitrary intensity correlations to the security analysis of decoy-state QKD. This technique only requires to experimentally quantify two main parameters: the correlation range and the maximum relative deviation between the selected and the actually emitted intensities. As a side contribution, we provide a non-standard derivation of the asymptotic secret key rate formula from the non-asymptotic one, in so revealing a necessary condition for the significance of the former.

Passive decoy-state quantum key distribution with imperfect source

Passive generation is a sophisticated way of state preparation in quantum key distribution (QKD) systems which is designed to exploit some internal physical process as a source of randomness. It can be profitable in a wide range of scenarios. However, the original analysis of the passive scheme implies an ideal interference which is almost impossible to assure in practice, therefore utilizing such method potentially compromises the security of the system. Here we develop a general technique to estimate decoy-state parameters for a passive protocol with an arbitrary experimental distribution of intensity. We compare this analysis with the original method and show that the proposed technique can provide higher key generation rates.

Complete Cohomology for Extriangulated Categories

Let [Formula: see text] be an extriangulated category with a proper class [Formula: see text] of [Formula: see text]-triangles. We study complete cohomology of objects in [Formula: see text] by applying [Formula: see text]-projective resolutions and [Formula: see text]-injective coresolutions constructed in [Formula: see text]. Vanishing of complete cohomology detects objects with finite [Formula: see text]-projective dimension and finite [Formula: see text]-injective dimension. As a consequence, we obtain some criteria for the validity of the Wakamatsu tilting conjecture and give a necessary and sufficient condition for a virtually Gorenstein algebra to be Gorenstein. Moreover, we give a general technique for computing complete cohomology of objects with finite [Formula: see text]-[Formula: see text]projective dimension. As an application, the relations between [Formula: see text]-projective dimension and [Formula: see text]-[Formula: see text]projective dimension for objects in [Formula: see text] are given.

Design and Implementation of Efficient MOSFET’s Utilization Based Proposed Voltage Controlled Oscillator

Ring oscillator is a device which consists of NOT gates connected in the form of ring. This ring oscillator’s output oscillates between the true and false stages controlled by applied voltage. Now days this voltage controlled oscillator (VCO) becomes the heart of modern electronic devices and communication systems. Earlier five-stage complementary metal oxide semiconductor (CMOS) based VCO for the Phase Locked Loop (PLL) was implemented. High frequency oscillations are required for many applications and further it is observed that a very general technique is normally adopted by researchers to achieve high frequency that if number of transistors is increased then the frequency can be increased. But the consequences of increase in number of transistors are the increase in delay and more number of MOSFET occupies more area and more power dissipation. So, in this paper VCO is designed with efficient utilization of MOSFETs. There is a balance between frequency and number of transistors, so that the area and power dissipation can be reduced. From the obtained results it can observed that the number of MOSFET’s, Independent Nodes, boundary nodes total nodes and power are reduced compared to five stage VCO and VCO based Ring oscillator.

Multiple imputation with missing data indicators

Multiple imputation is a well-established general technique for analyzing data with missing values. A convenient way to implement multiple imputation is sequential regression multiple imputation, also called chained equations multiple imputation. In this approach, we impute missing values using regression models for each variable, conditional on the other variables in the data. This approach, however, assumes that the missingness mechanism is missing at random, and it is not well-justified under not-at-random missingness without additional modification. In this paper, we describe how we can generalize the sequential regression multiple imputation imputation procedure to handle missingness not at random in the setting where missingness may depend on other variables that are also missing but not on the missing variable itself, conditioning on fully observed variables. We provide algebraic justification for several generalizations of standard sequential regression multiple imputation using Taylor series and other approximations of the target imputation distribution under missingness not at random. Resulting regression model approximations include indicators for missingness, interactions, or other functions of the missingness not at random missingness model and observed data. In a simulation study, we demonstrate that the proposed sequential regression multiple imputation modifications result in reduced bias in the final analysis compared to standard sequential regression multiple imputation, with an approximation strategy involving inclusion of an offset in the imputation model performing the best overall. The method is illustrated in a breast cancer study, where the goal is to estimate the prevalence of a specific genetic pathogenic variant.

Comprehensive deletion landscape of CRISPR-Cas9 identifies minimal RNA-guided DNA-binding modules

Proteins evolve through the modular rearrangement of elements known as domains. Extant, multidomain proteins are hypothesized to be the result of domain accretion, but there has been limited experimental validation of this idea. Here, we introduce a technique for genetic minimization by iterative size-exclusion and recombination (MISER) for comprehensively making all possible deletions of a protein. Using MISER, we generate a deletion landscape for the CRISPR protein Cas9. We find that the catalytically-dead Streptococcus pyogenes Cas9 can tolerate large single deletions in the REC2, REC3, HNH, and RuvC domains, while still functioning in vitro and in vivo, and that these deletions can be stacked together to engineer minimal, DNA-binding effector proteins. In total, our results demonstrate that extant proteins retain significant modularity from the accretion process and, as genetic size is a major limitation for viral delivery systems, establish a general technique to improve genome editing and gene therapy-based therapeutics.

The importance of local anesthesia in children in the general technique of biliary tract surgery

"A physician who finds a remedy that combines the advantages of ether and chloroform, without having their disadvantages, will be the BEST laparotomist of his time."