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We present OSTRICH2, the latest evolution of the SMT solver OSTRICH for string constraints. OSTRICH2 supports a wide range of complex functions on strings and provides completeness guarantees for a substantial fragment of string constraints, including the straight-line fragment and the chain-free fragment. OSTRICH2 provides full support for the SMT-LIB theory of Unicode strings, extending the standard with several unique features not found in other solvers: among others, parsing of ECMAScript regular expressions (including look-around assertions and capture groups) and handling of user-defined string transducers. We empirically demonstrate that OSTRICH2 is competitive to other string solvers on SMT-COMP benchmarks.
In biological systems, both skin sensitivity and body flexibility play crucial roles in haptic perception. Fully soft robots often suffer from structural fragility and delayed sensory processing, limiting their practical functionality. The musculoskeletal system combines the adaptability of soft materials with the durability of rigid-body robots. It also leverages morphological computation, where the morphological structures contribute to information processing, for dynamic and adaptive behaviors. This study focuses on the pecking behaviors of birds, which enables precise haptic perception through the musculoskeletal system of their flexible neck. Physical reservoir computing is applied to flexible structures inspired by an ostrich neck to analyze the relationship between haptic perception and physical characteristics. Experiments with both a physical robot and simulations reveal that, with appropriate viscoelasticity, the flexible structure can discriminate object softness and retain that information through behavior. Drawing on these findings and anatomical insights from the ostrich neck, a haptic perception system is proposed that exhibits both separability and behavioral memory
The Sauropoda were the largest terrestrial animals ever to have lived on this planet. As their nutritional requirements were so huge, their diet holds sway over the ecology of many Mesozoic herbivores. The diet of the sauropods is limited by their feeding envelope, which in turn is governed by the posture and flexibility of their elongate necks. Yet the exact nature of the flexibility and posture of the neck has been a contentious issue. Previous studies have utilised computer models of dry bone, mechanical principles or the flexibility of the necks of extant animals. However, the effect of the musculature of the neck has yet to be investigated. Through measurements of the flexibility of the ostrich neck after cumulative tissue removal, analyses of the muscle attachment sites of the ostrich and sauropods, and testing of the Osteological Neutral Pose model, this study attempts to rectify this situation. The ostrich neck was shown to have three sections of flexibility; a slightly flexible anterior section, a very flexible middle section and a stiff posterior section. The Osteological Neutral Pose did not show these sections, and was shown to potentially overestimate and underestimate
Muscle-actuated control is a research topic that spans multiple domains, including biomechanics, neuroscience, reinforcement learning, robotics, and graphics. This type of control is particularly challenging as bodies are often overactuated and dynamics are delayed and non-linear. It is however a very well tested and tuned actuation mechanism that has undergone millions of years of evolution with interesting properties exploiting passive forces and efficient energy storage of muscle-tendon units. To facilitate research on muscle-actuated simulation, we release a 3D musculoskeletal simulation of an ostrich based on the MuJoCo physics engine. The ostrich is one of the fastest bipeds on earth and therefore makes an excellent model for studying muscle-actuated bipedal locomotion. The model is based on CT scans and dissections used to collect actual muscle data, such as insertion sites, lengths, and pennation angles. Along with this model, we also provide a set of reinforcement learning tasks, including reference motion tracking, running, and neck control, used to infer muscle actuation patterns. The reference motion data is based on motion capture clips of various behaviors that we pre
End users' awareness about the data they share, the purpose of sharing that data, and their control over it, is key to establishing trust and eradicating privacy concerns. We experimented on personal data management by prototyping a Point-of-Interest recommender system in which data collected on the user can be viewed, edited, deleted, and shared via elements in the User Interface. Based on our qualitative findings, in this paper we discuss "The ostrich policy" adopted by end users who do not want to manage their personal data. We sound a waking whistle to design and model for personal data management by understanding end users' perceptions towards data transparency and control.
More than 60,000 years ago, humans in southern Africa were engraving ostrich eggshells with intricate geometric patterns that appear far more organized than previously realized。 Researchers found recurring grids, parallel lines, right angles, and repeated shapes, suggesting the designs followed deliberate rules rather than being improvised。 The eng
The theory of sequences, supported by many SMT solvers, can model program data types including bounded arrays and lists. Sequences are parameterized by the element data type and provide operations such as accessing elements, concatenation, forming sub-sequences and updating elements. Strings and sequences are intimately related; many operations, e.g., matching a string according to a regular expression, splitting strings, or joining strings in a sequence, are frequently used in string-manipulating programs. Nevertheless, these operations are typically not directly supported by existing SMT solvers, which instead only consider the generic theory of sequences. In this paper, we propose a theory of string sequences and study its satisfiability. We show that, while it is undecidable in general, the decidability can be recovered by restricting to the straight-line fragment. This is shown by encoding each string sequence as a string, and each string sequence operation as a corresponding string operation. We provide pre-image computation for the resulting string operations with respect to automata, effectively casting it into the generic OSTRICH string constraint solving framework. We imp
The past decade has witnessed substantial developments in string solving. Motivated by the complexity of string solving strategies adopted in existing string solvers, we investigate a simple and generic method for solving string constraints: regular constraint propagation. The method repeatedly computes pre- or post-images of regular languages under the string functions present in a string formula, inferring more and more knowledge about the possible values of string variables, until either a conflict is found or satisfiability of the string formula can be concluded. Such a propagation strategy is applicable to string constraints with multiple operations like concatenation, replace, and almost all flavors of string transductions. We demonstrate the generality and effectiveness of this method theoretically and experimentally. On the theoretical side, we show that RCP is sound and complete for a large fragment of string constraints, subsuming both straight-line and chain-free constraints, two of the most expressive decidable fragments for which some modern string solvers provide formal completeness guarantees. On the practical side, we implement regular constraint propagation within
This paper introduces a new type of soft continuum robot, called SCoReS, which is capable of self-controlling continuously its curvature at the segment level; in contrast to previous designs which either require external forces or machine elements, or whose variable curvature capabilities are discrete -- depending on the number of locking mechanisms and segments. The ability to have a variable curvature, whose control is continuous and independent from external factors, makes a soft continuum robot more adaptive in constrained environments, similar to what is observed in nature in the elephant's trunk or ostrich's neck for instance which exhibit multiple curvatures. To this end, our soft continuum robot enables reconfigurable variable curvatures utilizing a variable stiffness growing spine based on micro-particle granular jamming for the first time. We detail the design of the proposed robot, presenting its modeling through beam theory and FEA simulation -- which is validated through experiments. The robot's versatile bending profiles are then explored in experiments and an application to grasp fruits at different configurations is demonstrated.
Performing time-traversal queries on RDF datasets remains unsupported in the most extensive knowledge graphs. Existing solutions either require offline ingestion, which prevents concurrent querying and updating, or operate live but with limited query coverage or triplestore dependency. This article presents the Time Agnostic Library, a Python library for performing temporal SPARQL queries live on any SPARQL-compliant triplestore, supporting all six temporal retrieval needs identified in the literature and concurrent updates. The methodology builds on the OpenCitations Data Model (OCDM), which records provenance using the Provenance Ontology (PROV-O) and SPARQL UPDATE operations. The library supports version materialization, single-version and cross-version structured queries, delta materialization, and single-delta and cross-delta structured queries over multi-triple patterns. Evaluation on the BEAR-B benchmark shows sub-linear scaling in both execution time and memory consumption as the number of versions increases. While preprocessing-based systems such as OSTRICH achieve faster query times, they require offline ingestion and cannot handle concurrent data updates. Against R43ples
Machine learning models are vulnerable to adversarial examples: small changes to images can cause computer vision models to make mistakes such as identifying a school bus as an ostrich. However, it is still an open question whether humans are prone to similar mistakes. Here, we address this question by leveraging recent techniques that transfer adversarial examples from computer vision models with known parameters and architecture to other models with unknown parameters and architecture, and by matching the initial processing of the human visual system. We find that adversarial examples that strongly transfer across computer vision models influence the classifications made by time-limited human observers.
We investigate the twofold functionality of a cylindrical shell consisting of a negatively refracting heterogeneous bianisotropic (NRHB) medium deduced from geometric transforms. The numerical simulations indicate that the shell enhances their scattering by a perfect electric conducting (PEC) core, whereas it considerably reduces the scattering of electromagnetic waves by closely located dipoles when the shell surrounds a bianisotropic core. The former can be attributed to a homeopathic effect, whereby a small PEC object scatters like a large one as confirmed by numerics, while the latter can be attributed to space cancelation of complementary bianisotropic media underpinning anomalous resonances counteracting the field emitted by small objects (external cloaking). Space cancellation is further used to cloak a NRHB finite size object located nearby a slab of NRHB with a hole of same shape and opposite refracting index. Such a finite frequency external cloaking is also achieved with a NRHB cylindrical lens. Finally, we investigate an ostrich effect whereby the scattering of NRHB slab and cylindrical lenses with simplified parameters hide the presence of dipoles in the quasi-static l
In the task of image classification, usually, the network is sensitive to noises. For example, an image of cat with noises might be misclassified as an ostrich. Conventionally, to overcome the problem of noises, one uses the technique of data augmentation, that is, to teach the network to distinguish noises by adding more images with noises in the training dataset. In this work, we provide a noise-resistance network in images classification by introducing a technique of pixel embedding. We test the network with pixel embedding, which is abbreviated as the network with PE, on the mnist database of handwritten digits. It shows that the network with PE outperforms the conventional network on images with noises. The technique of pixel embedding can be used in many tasks of image classification to improve noise resistance.
We present a novel length-aware solving algorithm for the quantifier-free first-order theory over regex membership predicate and linear arithmetic over string length. We implement and evaluate this algorithm and related heuristics in the Z3 theorem prover. A crucial insight that underpins our algorithm is that real-world instances contain a wealth of information about upper and lower bounds on lengths of strings under constraints, and such information can be used very effectively to simplify operations on automata representing regular expressions. Additionally, we present a number of novel general heuristics, such as the prefix/suffix method, that can be used in conjunction with a variety of regex solving algorithms, making them more efficient. We showcase the power of our algorithm and heuristics via an extensive empirical evaluation over a large and diverse benchmark of 57256 regex-heavy instances, almost 75% of which are derived from industrial applications or contributed by other solver developers. Our solver outperforms five other state-of-the-art string solvers, namely, CVC4, OSTRICH, Z3seq, Z3str3, and Z3-Trau, over this benchmark, in particular achieving a 2.4x speedup over
Scientists have created the first quantum material that can sort and transport different quantum states of light at room temperature, potentially removing the need for bulky, ultra-cold refrigeration systems。 Built from a gold film carved with hundreds of microscopic structures, the ultrathin “metacrystal” acts like a filter that directs different
A new hollow nanoreactor mimics living cells to make hydrogen peroxide more efficiently using visible light。 Its light-trapping cavity and proton-shuttling shell could open new possibilities for cleaner chemical manufacturing and artificial photosynthesis
Scientists have demonstrated that heat can move through a crystal in focused, wave-like rays at room temperature instead of spreading randomly。 The breakthrough could make it possible to route heat around sensitive parts of next-generation chips and quantum devices