1,205 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Expanding Clinical Knowledge and Awareness to Non-Benzodiazepine Treatments by Providing an Educational Intervention: A Quantitative Study

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    This study examined the effectiveness of an educational intervention for healthcare clinicians to increase knowledge and awareness of non-benzodiazepine treatments for the treatment of anxiety and panic disorders. The target population were healthcare clinicians in a metropolitan area that commonly treat anxiety and panic disorders. Clinicians from different specialties were recruited to participate and evaluated on their knowledge of benzodiazepines on a 3-question pretest survey using a Likert scale. The clinician was then given a 30-minute educational intervention that covered the risks and dangers of benzodiazepines and a review of alternative, non-benzodiazepine treatment options. The clinician then self-evaluated themselves using a similar 3-question posttest survey. The results were examined to determine the effectiveness of the educational intervention in changing clinical practice

    Linearly-Homomorphic Signatures for Short Randomizable Proofs of Subset Membership

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    Electronic voting is one of the most interesting application of modern cryptography, as it involves many innovative tools (such as homomorphic public-key encryption, non-interactive zero-knowledge proofs, and distributed cryptography) to guarantee several a priori contradictory security properties: the integrity of the tally and the privacy of the individual votes. While many efficient solutions exist for honest-but-curious voters, that follow the official procedure but try to learn more than just the public result, preventing attacks from malicious voters is much more complex: when voters may have incentive to send biased ballots, the privacy of the ballots is much harder to satisfy, whereas this is the crucial security property for electronic voting. We present a new technique to prove that an ElGamal ciphertext contains a message from a specific subset (quasi-adaptive NIZK of subset membership), using linearly-homomorphic signatures. The proofs are both quite efficient to generate, allowing the use of low-power devices to vote, and randomizable, which is important for the strong receipt-freeness property. They are well-suited to prevent vote-selling and replay attacks, which are the main threats against the privacy in electronic voting, with security proofs in the generic group model and the random oracle model

    Properly Learning Decision Trees with Queries Is NP-Hard

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    We prove that it is NP-hard to properly PAC learn decision trees with queries, resolving a longstanding open problem in learning theory (Bshouty 1993; Guijarro-Lavin-Raghavan 1999; Mehta-Raghavan 2002; Feldman 2016). While there has been a long line of work, dating back to (Pitt-Valiant 1988), establishing the hardness of properly learning decision trees from random examples, the more challenging setting of query learners necessitates different techniques and there were no previous lower bounds. En route to our main result, we simplify and strengthen the best known lower bounds for a different problem of Decision Tree Minimization (Zantema-Bodlaender 2000; Sieling 2003). On a technical level, we introduce the notion of hardness distillation, which we study for decision tree complexity but can be considered for any complexity measure: for a function that requires large decision trees, we give a general method for identifying a small set of inputs that is responsible for its complexity. Our technique even rules out query learners that are allowed constant error. This contrasts with existing lower bounds for the setting of random examples which only hold for inverse-polynomial error. Our result, taken together with a recent almost-polynomial time query algorithm for properly learning decision trees under the uniform distribution (Blanc-Lange-Qiao-Tan 2022), demonstrates the dramatic impact of distributional assumptions on the problem.Comment: 41 pages, 10 figures, FOCS 202

    International consensus statement on allergy and rhinology: Allergic rhinitis – 2023

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    Background In the 5 years that have passed since the publication of the 2018 International Consensus Statement on Allergy and Rhinology: Allergic Rhinitis (ICAR-Allergic Rhinitis 2018), the literature has expanded substantially. The ICAR-Allergic Rhinitis 2023 update presents 144 individual topics on allergic rhinitis (AR), expanded by over 40 topics from the 2018 document. Originally presented topics from 2018 have also been reviewed and updated. The executive summary highlights key evidence-based findings and recommendation from the full document. Methods ICAR-Allergic Rhinitis 2023 employed established evidence-based review with recommendation (EBRR) methodology to individually evaluate each topic. Stepwise iterative peer review and consensus was performed for each topic. The final document was then collated and includes the results of this work. Results ICAR-Allergic Rhinitis 2023 includes 10 major content areas and 144 individual topics related to AR. For a substantial proportion of topics included, an aggregate grade of evidence is presented, which is determined by collating the levels of evidence for each available study identified in the literature. For topics in which a diagnostic or therapeutic intervention is considered, a recommendation summary is presented, which considers the aggregate grade of evidence, benefit, harm, and cost. Conclusion The ICAR-Allergic Rhinitis 2023 update provides a comprehensive evaluation of AR and the currently available evidence. It is this evidence that contributes to our current knowledge base and recommendations for patient evaluation and treatment

    An Examination Of High School Music Course Offerings In Virginia: A Mixed Methods Study

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    High school music education is not mandated by the Standards of Quality, the Virginia state educational law, and courses offered on the high school level vary among Virginia school divisions. This explanatory mixed methods dissertation study provides an overview of history of development of high school music education in Virginia, reveals what high school music courses currently offered in Virginia school divisions (N = 131), and surveys approaches to development of programs of studies of a representative sample of Virginia school divisions (n = 14). The study generated three major findings. First, 29 various courses are offered among Virginia school divisions on various levels, five performance type courses and five nonperformance type courses. Out of ten course types offered in Virginia, Band and Chorus are the only courses offered at significantly high rates, while Composition, Guitar, Music Technology, IB Music, Orchestra, and Piano are offered at significantly low rates. This is because Band and Chorus have traditionally been considered as basic high school music courses, and everything else is offered as school divisions can afford and what teachers employed in school divisions can teach. Second, larger Virginia school divisions, located in racially/ethnically diverse cities and suburbs offer more variety of high school music courses. This is because low school budgets and teacher shortages are detrimental to smaller and remote school divisions, as they can afford to hire only so many teachers to teach only so many subjects. Third, administrative approaches to developing high school programs of studies, particularly approaches to stakeholder engagement in program development, influence what courses are offered

    Synthase-selected sorting approach identifies a beta-lactone synthase in a nudibranch symbiotic bacterium

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    [Background] Nudibranchs comprise a group of > 6000 marine soft-bodied mollusk species known to use secondary metabolites (natural products) for chemical defense. The full diversity of these metabolites and whether symbiotic microbes are responsible for their synthesis remains unexplored. Another issue in searching for undiscovered natural products is that computational analysis of genomes of uncultured microbes can result in detection of novel biosynthetic gene clusters; however, their in vivo functionality is not guaranteed which limits further exploration of their pharmaceutical or industrial potential. To overcome these challenges, we used a fluorescent pantetheine probe, which produces a fluorescent CoA-analog employed in biosynthesis of secondary metabolites, to label and capture bacterial symbionts actively producing these compounds in the mantle of the nudibranch Doriopsilla fulva.[Results] We recovered the genome of Candidatus Doriopsillibacter californiensis from the Ca. Tethybacterales order, an uncultured lineage of sponge symbionts not found in nudibranchs previously. It forms part of the core skin microbiome of D. fulva and is nearly absent in its internal organs. We showed that crude extracts of D. fulva contained secondary metabolites that were consistent with the presence of a beta-lactone encoded in Ca. D. californiensis genome. Beta-lactones represent an underexplored group of secondary metabolites with pharmaceutical potential that have not been reported in nudibranchs previously.[Conclusions] Altogether, this study shows how probe-based, targeted sorting approaches can capture bacterial symbionts producing secondary metabolites in vivo.The work (proposal: 10.46936/10.25585/60000940) conducted by the U.S. Department of Energy Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science User Facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231. RS, MB, JL, and TW are supported by NIH grant R01AI168993. The John Templeton Foundation (grant nos. 51250 and 60973) supported TT and SVD, and the Gordon and Betty Moore Foundation grants (GBMF7617 and GBMF9340) supported SVD. MD is supported by the Generalitat Valenciana program GenT grant number CDEIGENT/2021/008. SPE is supported by a FPU grant from the Spanish Ministry of Universities (Reference: FPU20/05756).Peer reviewe

    A Survey on Low-Power GNSS

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    With the miniaturization of electronics, Global Navigation Satellite Systems (GNSS) receivers are getting more and more embedded into devices with harsh energy constraints. This process has led to new signal processing challenges due to the limited processing power on battery-operated devices and to challenging wireless environments, such as deep urban canyons, tunnels and bridges, forest canopies, increased jamming and spoofing. The latter is typically tackled via new GNSS constellations and modernization of the GNSS signals. However, the increase in signal complexity leads to higher computation requirements to recover the signals; thus, the trade-off between precision and energy should be evaluated for each application. This paper dives into low-power GNSS, focusing on the energy consumption of satellite-based positioning receivers used in battery-operated consumer devices and Internet of Things (IoT) sensors. We briefly overview the GNSS basics and the differences between legacy and modernized signals. Factors dominating the energy consumption of GNSS receivers are then reviewed, with special attention given to the complexity of the processing algorithms. Onboard and offloaded (Cloud/Edge) processing strategies are explored and compared. Finally, we highlight the current challenges of today’s research in low-power GNSS.Peer reviewe

    Fundamentals of Clustered Molecular Nanonetworks

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    We present a comprehensive approach to the modeling, performance analysis, and design of clustered molecular nanonetworks in which nano-machines of different clusters release an appropriate number of molecules to transmit their sensed information to their respective fusion centers. The fusion centers decode this information by counting the number of molecules received in the given time slot. Owing to the propagation properties of the biological media, this setup suffers from both inter- and intra-cluster interference that needs to be carefully modeled. To facilitate rigorous analysis, we first develop a novel spatial model for this setup by modeling nano-machines as a Poisson cluster process with the fusion centers forming its parent point process. For this setup, we first derive a new set of distance distributions in the three-dimensional space, resulting in a remarkably simple result for the special case of the Thomas cluster process. Using this, total interference from previous symbols and different clusters is characterized and its expected value and Laplace transform are obtained. The error probability of a simple detector suitable for biological applications is analyzed, and approximate and upper-bound results are provided. The impact of different parameters on the performance is also investigated.Comment: Accepted for publicatio

    Refining the Adaptivity Notion in the Huge Object Model

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    The Huge Object model for distribution testing, first defined by Goldreich and Ron in 2022, combines the features of classical string testing and distribution testing. In this model we are given access to independent samples from an unknown distribution PP over the set of strings {0,1}n\{0,1\}^n, but are only allowed to query a few bits from the samples. The distinction between adaptive and non-adaptive algorithms, which is natural in the realm of string testing (but is not relevant for classical distribution testing), plays a substantial role in the Huge Object model as well. In this work we show that in fact, the full picture in the Huge Object model is much richer than just that of the ``adaptive vs. non-adaptive'' dichotomy. We define and investigate several models of adaptivity that lie between the fully-adaptive and the completely non-adaptive extremes. These models are naturally grounded by viewing the querying process from each sample independently, and considering the ``algorithmic flow'' between them. For example, if we allow no information at all to cross over between samples (up to the final decision), then we obtain the locally bounded adaptive model, arguably the ``least adaptive'' one apart from being completely non-adaptive. A slightly stronger model allows only a ``one-way'' information flow. Even stronger (but still far from being fully adaptive) models follow by taking inspiration from the setting of streaming algorithms. To show that we indeed have a hierarchy, we prove a chain of exponential separations encompassing most of the models that we define
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