Genies, lawyers, and smart-asses: Extending proxy failures to intentional misunderstandings.

We propose that the logic of a genie - an agent that exploits an ambiguous request to intentionally misunderstand a stated goal - underlies a common and consequential phenomenon, well within what is currently called proxy failures. We argue that such intentional misunderstandings are not covered by the current proposed framework for proxy failures, and suggest to expand it.

Leveraging logical definitions and lexical features to detect missing IS-A relations in biomedical terminologies.

Biomedical terminologies play a vital role in managing biomedical data. Missing IS-A relations in a biomedical terminology could be detrimental to its downstream usages. In this paper, we investigate an approach combining logical definitions and lexical features to discover missing IS-A relations in two biomedical terminologies: SNOMED CT and the National Cancer Institute (NCI) thesaurus. The method is applied to unrelated concept-pairs within non-lattice subgraphs: graph fragments within a terminology likely to contain various inconsistencies. Our approach first compares whether the logical definition of a concept is more general than  that of the other concept. Then, we check whether the lexical features of the concept are contained in those of the other concept. If both constraints are satisfied, we suggest a potentially missing IS-A relation between the two concepts. The method identified 982 potential missing IS-A relations for SNOMED CT and 100 for NCI thesaurus. In order to assess the efficacy of our approach, a random sample of results belonging to the "Clinical Findings" and "Procedure" subhierarchies of SNOMED CT and results belonging to the "Drug, Food, Chemical or Biomedical Material" subhierarchy of the NCI thesaurus were evaluated by domain experts. The evaluation results revealed that 118 out of 150 suggestions are valid for SNOMED CT and 17 out of 20 are valid for NCI thesaurus.

Causal inference in ethnographic research: Refining explanations with abductive logic, strength of evidence assessments, and graphical models.

In their classic accounts, anthropological ethnographers developed causal arguments for how specific sociocultural structures and processes shaped human thought, behavior, and experience in particular settings. Despite this history, many contemporary ethnographers avoid establishing in their work direct causal relationships between key variables in the way that, for example, quantitative research relying on experimental or longitudinal data might. As a result, ethnographers in anthropology and other fields have not advanced understandings of how to derive causal explanations from their data, which contrasts with a vibrant "causal revolution" unfolding in the broader social and behavioral sciences. Given this gap in understanding, we aim in the current article to clarify the potential ethnography has for illuminating causal processes related to the cultural influence on human knowledge and practice. We do so by drawing on our ongoing mixed methods ethnographic study of games, play, and avatar identities. In our ethnographic illustrations, we clarify points often left unsaid in both classic anthropological ethnographies and in more contemporary interdisciplinary theorizing on qualitative research methodologies. More specifically, we argue that for ethnographic studies to illuminate causal processes, it is helpful, first, to state the implicit strengths and logic of ethnography and, second, to connect ethnographic practice more fully to now well-developed interdisciplinary approaches to causal inference. In relation to the first point, we highlight the abductive inferential logic of ethnography. Regarding the second point, we connect the ethnographic logic of abduction to what Judea Pearl has called the ladder of causality, where moving from association to intervention to what he calls counterfactual reasoning produces stronger evidence for causal processes. Further, we show how graphical modeling approaches to causal explanation can help ethnographers clarify their thinking. Overall, we offer an alternative vision of ethnography, which contrasts, but nevertheless remains consistent with, currently more dominant interpretive approaches.

Learning the Meanings of Function Words From Grounded Language Using a Visual Question Answering Model.

Interpreting a seemingly simple function word like "or," "behind," or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior acquisition theories have often relied on positing a foundation of innate knowledge. Yet recent neural-network-based visual question answering models apparently can learn to use function words as part of answering questions about complex visual scenes. In this paper, we study what these models learn about function words, in the hope of better understanding how the meanings of these words can be learned by both models and children. We show that recurrent models trained on visually grounded language learn gradient semantics for function words requiring spatial and numerical reasoning. Furthermore, we find that these models can learn the meanings of logical connectives and and or without any prior knowledge of logical reasoning as well as early evidence that they are sensitive to alternative expressions when interpreting language. Finally, we show that word learning difficulty is dependent on the frequency of models' input. Our findings offer proof-of-concept evidence that it is possible to learn the nuanced interpretations of function words in a visually grounded context by using non-symbolic general statistical learning algorithms, without any prior knowledge of linguistic meaning.

Light-triggered AND logic tetrapeptide dynamic covalent assembly.

We demonstrate light-triggered dynamic covalent assembly of a linear short tetrapeptide containing two terminal cysteine residues in an AND logic manner. A photobase generator is introduced to accomplish light-mediated pH regulation to increase the reduction potential of thiols in the tetrapeptide, which activates its oxidative polymerization through disulfide bonds. Interestingly, it is elucidated that under light irradiation, mere co-existence of photobase generator and the oxidizing agent permits the polymerization performance of this tetrapeptide. Hence, a light-triggered AND logic dynamic covalent assembly of a tetrapeptide is achieved. Further, upon redox response, the reversible aggregation and disaggregation can be transformed for numerous times due to the dynamic covalent feature of disulfide bond. As a comparison, no assembly occurs for a short peptide containing one terminal cysteine residue under the same stimuli condition. This work offers a new approach to remotely control programmable molecular assembly of short linear peptides based on dynamic covalent bond, holding great potential in wide bioapplications.

Exploring the decision-making process of female genital cosmetic procedures in Iranian women and constructing and validating a results-based logic model for a healthy public policy: a study protocol.

BACKGROUND: Female genital cosmetic procedures have grown rapidly in most parts of the world. Professional organizations have issued warnings about the complications and long-term consequences of these practices. To be able to adopt the right health policies, it is necessary to know why women decide to perform these procedures. Therefore, the present study will be aim to discover the decision-making process involved in performing female genital cosmetic procedures for Iranian women and construct and validate a results-based logic model for healthy public policy. METHODS: The present study was conducted in three phases. In the initial phase, a qualitative study will be conducted with the Corbin and Strauss ground theory approach. The participants in the study will be healthy women who desire or have undergone female genital cosmetic procedures without medical indications. In this phase, purposive and theoretical sampling will guide recruitment and data collection. The data will be collected via semi-structured interviews, field notes and observations of individual interactions. The data will be analysed using the approach of Corbin and Strauss (2015). MAXQDA 2007 software was used for managing the process of data analysis. In the second phase, the development of a results-based logic model for a healthy public policy is performed based on the findings of the first phase of the study, interviews with key informants and a review of the results of the literature in this field. Finally, validation of the designed program will be performed by the nominal group technique with the presence of a group of experts in the third phase. DISCUSSION: The findings of this study, by identifying women's main concerns related to the studied phenomenon, the existing context, participants' reactions and the consequences of the adopted reactions, can be very important in designing a program that fits Iran's cultural characteristics. In this research, a program using a logical model will be presented that is suitable for policymakers, planners and healthcare service providers to be implemented in the social-cultural context of the study.

Female genital cosmetic procedures refer to a group of cosmetic procedures that change the structure and healthy appearance of the female external genitalia to improve sexual performance or body image. The desire to perform these techniques has become popular in most parts of the world. However, scientific societies have warned about the efficiency, effectiveness and side effects of these techniques. According to these points, the present study aims to discover the decision-making process of performing FGCPs for Iranian women and to construct and validate a program for healthy public policy. This study will be performed in three stages. First, a qualitative study and interviews with healthy women who desire or have undergone female genital cosmetic procedures will be performed. In the following, based on the findings of the first stage, interviews with key informants and a review of literature, a program will be presented to reduce or prevent these procedures, and then this program will be validated. Using the designed program, healthcare practitioners will be able to provide women with more effective advice and guidance to make correct and informed decisions. In addition, this program will enable planners and policymakers to take steps to reduce the demand for these actions and make informed decisions by women by changing and adjusting the conditions and context.

Eu(III) functionalized ZnMOF based efficient dual-emission sensor integrated with self-calibrating logic gate for intelligent detection of epinephrine.

The rapid detection of epinephrine (EPI) in serum holds immense importance in the early disease diagnosis and regular monitoring. On the basis of the coordination post-synthetic modification (PSM) strategy, a Eu3+ functionalized ZnMOF (Eu3+@ZnMOF) was fabricated by anchoring the Eu3+ ions within the microchannels of ZnMOF as secondary luminescent centers. Benefiting from two independent luminescent centers, the prepared Eu3+@ZnMOF shows great potential as a multi-signal self-calibrating luminescent sensor in visually and efficiently detecting serum EPI levels, with high reliability, fast response time, excellentrecycleability, and low detection limits of 17.8 ng/mL. Additionally, an intelligent sensing system was designed in accurately and reliably detecting serum EPI levels, based on the designed self-calibrating logic gates. Furthermore, the possible sensing mechanisms were elucidated through theoretical calculations as well as spectral overlaps. This work provides an effective and promising strategy for developing MOFs-based self-calibrating intelligent sensing platforms to detect bioactive molecules in bodily fluids.

LollipopE: Bi-centered lollipop embedding for complex logic query on knowledge graph.

Answering complex First-Order Logic (FOL) query plays a vital role in multi-hop knowledge graph (KG) reasoning. Geometric methods have emerged as a promising category of approaches in this context. However, existing best-performing geometric query embedding (QE) model is still up against three-fold potential problems: (i) underutilization of embedding space, (ii) overreliance on angle information, (iii) uncaptured hierarchy structure. To bridge the gap, we propose a lollipop-like bi-centered query embedding method named LollipopE. To fully utilize embedding space, LollipopE employs learnable centroid positions to represent multiple entities distributed along the same axis. To address the potential overreliance on angular metrics, we design an angular-based and centroid-based metric. This involves calculating both an angular distance and a centroid-based geodesic distance, which empowers the model to make more informed selections of relevant answers from a wider perspective. To effectively capture the hierarchical relationships among entities within the KG, we incorporate dynamic moduli, which allows for the representation of the hierarchical structure among entities. Extensive experiments demonstrate that LollipopE surpasses the state-of-the-art geometric methods. Especially, on more hierarchical datasets, LollipopE achieves the most significant improvement.

Latent Toehold-Mediated DNA Circuits Based on a Bulge-Loop Structure for Leakage Reduction and Its Application to Signal-Amplifying DNA Logic Gates.

DNA circuits based on successive toehold-mediated DNA displacement reactions, particularly entropy-driven DNA circuit (EDC) systems, have attracted considerable attention as powerful enzyme-free tools for dynamic DNA nanotechnology. However, background leakage (noise signal) often occurs when the circuit is executed nonspecifically, even in the absence of the appropriate catalyst DNA (input). This study designed and developed a new latent toehold-mediated DNA circuit (LDC) system that relies on a bulge-loop structure as a latent toehold toward leakage reduction. Furthermore, the number (size) of nucleotides (nt) in the bulge-loop is found to play a significant role in the performance (i.e., leakage, signal, and kinetics) of LDC systems. In fact, the signal rate for the LDC systems increased as the number of nt in the bulge-loop increased from 4 to 8, whereas the leakage rate of the LDC systems with bulge-loops of 7 nt or less was low, but the leakage rate of the LDC system with a bulge-loop of 8 nt increased significantly. Note that the LDC system with the optimal bulge-loop (7 nt) was capable of not only reducing the leakage but also accelerating the circuit speed without any signal loss, unlike methods of reducing the leakage by reducing the signal reported previously for the conventional EDC systems. These facts indicate that the 7 nt bulge-loop acts as a "latent" toehold for the DNA circuit system. By using the amplification function of output signals with an accelerated circuit and reduced leakage, our LDC system with a 7 nt bulge-loop could be applied directly and successfully to signal-amplifying DNA logic gates such as OR and AND gates, and thus, sufficient output signals could be obtained even with a small amount of input. These findings reveal that our LDC systems with a bulge-loop structure can replace the conventional EDC system and have enormous potential in the field of DNA nanotechnology.

A nanozyme with switchable enzyme-like activity for the logic gates detection of thymol and hydrogen peroxide in honey.

A new nanozyme (CuGaa) with switchable enzyme-like activity of peroxidase and polyphenol oxidase was successfully prepared based on guanidinoacetic acid and copper. The two enzyme-like activities can be easily switched by changing temperature or adding MnCl2. At 4 °C, polyphenol oxidase-like activity decreased to nearly 1%, and the material is mainly characterized by peroxidase-like activity at this point. However, at 60 °C in the presence of 20 mM MnCl2, the peroxidase-like activity decreased to nearly 10%, and the polyphenol oxidase-like activity of the materials increased to 140%. Based on the switchable enzyme-like activity of CuGaa, detection methods for thymol and hydrogen peroxide were developed. In addition, a rapid combination strategy was further established combined with logic gate technology for the facile identification of complex contamination in honey, which provided new ideas for low-cost and rapid honey identification.

Governing principles of transcriptional logic out of equilibrium.

To survive, adapt, and develop, cells respond to external and internal stimuli by tightly regulating transcription. Transcriptional regulation involves the combinatorial binding of a repertoire of transcription factors to DNA, which often results in switch-like binary outputs akin to Boolean logic gates. Recent experimental studies have demonstrated that in eukaryotes, transcription factor binding to DNA often involves energy expenditure, thereby driving the system out of equilibrium. The governing principles of transcriptional logic operations out of equilibrium remain unexplored. Here, we employ a simple two-input, single-locus model of transcription that can accommodate both equilibrium and nonequilibrium mechanisms. Using this model, we find that nonequilibrium regimes can give rise to all the logic operations accessible in equilibrium. Strikingly, energy expenditure alters the regulatory function of the two transcription factors in a mutually exclusive manner. This allows for the emergence of new logic operations that are inaccessible in equilibrium. Overall, our results show that energy expenditure can expand the range of cellular decision-making without the need for more complex promoter architectures.

Preponderance of generalized chain functions in reconstructed Boolean models of biological networks.

Boolean networks (BNs) have been extensively used to model gene regulatory networks (GRNs). The dynamics of BNs depend on the network architecture and regulatory logic rules (Boolean functions (BFs)) associated with nodes. Nested canalyzing functions (NCFs) have been shown to be enriched among the BFs in the large-scale studies of reconstructed Boolean models. The central question we address here is whether that enrichment is due to certain sub-types of NCFs. We build on one sub-type of NCFs, the chain functions (or chain-0 functions) proposed by Gat-Viks and Shamir. First, we propose two other sub-types of NCFs, namely, the class of chain-1 functions and generalized chain functions, the union of the chain-0 and chain-1 types. Next, we find that the fraction of NCFs that are chain-0 (also holds for chain-1) functions decreases exponentially with the number of inputs. We provide analytical treatment for this and other observations on BFs. Then, by analyzing three different datasets of reconstructed Boolean models we find that generalized chain functions are significantly enriched within the NCFs. Lastly we illustrate that upon imposing the constraints of generalized chain functions on three different GRNs we are able to obtain biologically viable Boolean models.

Neural flip-flops I: Short-term memory.

The networks proposed here show how neurons can be connected to form flip-flops, the basic building blocks in sequential logic systems. The novel neural flip-flops (NFFs) are explicit, dynamic, and can generate known phenomena of short-term memory. For each network design, all neurons, connections, and types of synapses are shown explicitly. The neurons' operation depends only on explicitly stated, minimal properties of excitement and inhibition. This operation is dynamic in the sense that the level of neuron activity is the only cellular change, making the NFFs' operation consistent with the speed of most brain functions. Memory tests have shown that certain neurons fire continuously at a high frequency while information is held in short-term memory. These neurons exhibit seven characteristics associated with memory formation, retention, retrieval, termination, and errors. One of the neurons in each of the NFFs produces all of the characteristics. This neuron and a second neighboring neuron together predict eight unknown phenomena. These predictions can be tested by the same methods that led to the discovery of the first seven phenomena. NFFs, together with a decoder from a previous paper, suggest a resolution to the longstanding controversy of whether short-term memory depends on neurons firing persistently or in brief, coordinated bursts. Two novel NFFs are composed of two and four neurons. Their designs follow directly from a standard electronic flip-flop design by moving each negation symbol from one end of the connection to the other. This does not affect the logic of the network, but it changes the logic of each component to a logic function that can be implemented by a single neuron. This transformation is reversible and is apparently new to engineering as well as neuroscience.

A Self-Similarity Logic May Shape the Organization of the Nervous System.

From the morphological point of view, the nervous system exhibits a fractal, self-similar geometry at various levels of observations, from single cells up to cell networks. From the functional point of view, it is characterized by a hierarchical organization in which self-similar structures (networks) of different miniaturizations are nested within each other. In particular, neuronal networks, interconnected to form neuronal systems, are formed by neurons, which operate thanks to their molecular networks, mainly having proteins as components that via protein-protein interactions can be assembled in multimeric complexes working as micro-devices. On this basis, the term "self-similarity logic" was introduced to describe a nested organization where, at the various levels, almost the same rules (logic) to perform operations are used. Self-similarity and self-similarity logic both appear to be intimately linked to the biophysical evidence for the nervous system being a pattern-forming system that can flexibly switch from one coherent state to another. Thus, they can represent the key concepts to describe its complexity and its concerted, holistic behavior.

Low-power and area-efficient memristor based non-volatile D latch and flip-flop: Design and analysis.

In recent years, non-volatile memory elements have become highly appealing for memory applications to implement a new class of storage memory that could replace flash memories in sequential logic applications, with features such as compactness, low power, fast processing speed, high endurance, and retention. The memristor is one such non-volatile element that fits the fundamental blocks of sequential logic circuits, the latch and flip-flop; hence, in this article, a non-volatile latch architecture using memristor ratioed logic (MRL) inverter and CMOS components is focused, with an additional memristor as a memory element. A Verilog-A model was used to create the memristor element. The simulation findings validated the compact, low-voltage, and reliable design of the latch design. We evolved in technology enough to create a master-slave flip-flop and arrange it to function as a counter and a shift register. Power, number of elements, cell size, energy, programming time, and robustness are compared to comparable non-volatile topologies. The proposed non-volatile latch proves non-volatility and can store data with a 24% reduction in power consumption and a near 10% reduction in area.

pH-dependent complex formation with TAR RNA and DNA: application towards logic gates.

Nucleic acid-based logic gates have shown great potential in biotechnology, medicine as well as diagnostics. Herein, we have constructed pH-responsive logic devices by utilizing HIV-1 TAR hairpins in combination with a thiazole peptide that exhibits turn-on fluorescence upon interacting with TAR RNA or DNA. Based on this, INHIBIT-AND and YES-INHIBIT-AND logic gates were constructed in parallel. The pH alteration leads to conformational changes of the hairpin structure, enabling the construction of a multi-reset reusable logic system which could be developed for in vitro sensing of the HIV-1 viral RNA.

A DNA tetrahedron dimer for dual membrane protein logic recognition and interaction inhibition.

Here, we report a DNA tetrahedron dimer for dual membrane protein logic recognition and interaction inhibition. The DNA tetrahedron dimer not only detects dual proteins that are both overexpressed on target cells in "AND" logic, but also inhibits protein interaction by steric hindrance to suppress cell proliferation, offering new insights for cancer cell diagnosis and treatment.

Bayesian-knowledge driven ontologies: A framework for fusion of semantic knowledge under uncertainty and incompleteness.

The modeling of uncertain information is an open problem in ontology research and is a theoretical obstacle to creating a truly semantic web. Currently, ontologies often do not model uncertainty, so stochastic subject matter must either be normalized or rejected entirely. Because uncertainty is omnipresent in the real world, knowledge engineers are often faced with the dilemma of performing prohibitively labor-intensive research or running the risk of rejecting correct information and accepting incorrect information. It would be preferable if ontologies could explicitly model real-world uncertainty and incorporate it into reasoning. We present an ontology framework which is based on a seamless synthesis of description logic and probabilistic semantics. This synthesis is powered by a link between ontology assertions and random variables that allows for automated construction of a probability distribution suitable for inferencing. Furthermore, our approach defines how to represent stochastic, uncertain, or incomplete subject matter. Additionally, this paper describes how to fuse multiple conflicting ontologies into a single knowledge base that can be reasoned with using the methods of both description logic and probabilistic inferencing. This is accomplished by using probabilistic semantics to resolve conflicts between assertions, eliminating the need to delete potentially valid knowledge and perform consistency checks. In our framework, emergent inferences can be made from a fused ontology that were not present in any of the individual ontologies, producing novel insights in a given domain.

DNA Logic Gates Integrated on DNA Substrates in Molecular Computing.

Due to nucleic acid's programmability, it is possible to realize DNA structures with computing functions, and thus a new generation of molecular computers is evolving to solve biological and medical problems. Pioneered by Milan Stojanovic, Boolean DNA logic gates created the foundation for the development of DNA computers. Similar to electronic computers, the field is evolving towards integrating DNA logic gates and circuits by positioning them on substrates to increase circuit density and minimize gate distance and undesired crosstalk. In this minireview, we summarize recent developments in the integration of DNA logic gates into circuits localized on DNA substrates. This approach of all-DNA integrated circuits (DNA ICs) offers the advantages of biocompatibility, increased circuit response, increased circuit density, reduced unit concentration, facilitated circuit isolation, and facilitated cell uptake. DNA ICs can face similar challenges as their equivalent circuits operating in bulk solution (bulk circuits), and new physical challenges inherent in spatial localization. We discuss possible avenues to overcome these obstacles.

An investigation of the effect of logical structures on Chinese preschool children's counterfactual reasoning development.

Counterfactual reasoning helps people to learn from the past to prepare for the future. In contrast to English with counterfactual markers that directly signal counterfactual reasoning, Mandarin Chinese indicates counterfactual reasoning by counterfactuality enhancers, which enhance rather than directly signal entry into the counterfactual realm. There are more counterfactuality enhancers in subtractive than additive counterfactual premises. Hence, Chinese-speaking children might more readily interpret subtractive than additive counterfactual premises, leading to better performance on subtractive than additive counterfactual reasoning tasks. This difference between logical structures might be larger in Chinese than English, as English has counterfactual markers, which enable direct inference of counterfactuality regardless of logical structures. Consistent with these propositions, in two experiments, the present study found that Chinese preschool children's accuracy was significantly higher for subtractive than additive counterfactual reasoning. Also, the difference between logical structures was much larger compared to a previous study in UK children using a similar counterfactual reasoning task. Hence, the use of counterfactuality enhancers in Chinese might shape a developmental difference between subtractive and additive counterfactual reasoning. Parents and teachers may attend to this developmental pattern when scaffolding children's counterfactual reasoning growth.