Detecting Unsolvability Based on Separating Functions

While the unsolvability IPC sparked a multitude of planners proficient in detecting unsolvable planning tasks, there are gaps where concise unsolvability arguments are known but no existing planner can capture them without prohibitive computational effort. One such example is the sliding tiles puzzle, where solvability can be decided in polynomial time with a parity argument. We introduce separating functions, which can prove that one state is unreachable from another, and show under what conditions a potential function over any nonzero ring is a separating function. We prove that we can compactly encode these conditions for potential functions over features that are pairs, and show in which cases we can efficiently synthesize functions satisfying these conditions. We experimentally evaluate a domain-independent algorithm that successfully synthesizes such separating functions from PDDL representations of the sliding tiles puzzle, the Lights Out puzzle, and Peg Solitaire

Optimality Certificates for Classical Planning

Algorithms are usually shown to be correct on paper, but bugs in their implementations can still lead to incorrect results. In the case of classical planning, it is fortunately straightforward to check whether a computed plan is correct. For optimal planning however, plans are additionally required to have minimal cost, which is significantly more difficult to verify. While some domain-specific approaches exists, we lack a general tool to verify optimality for arbitrary problems. We bridge this gap and introduce two approaches based on the principle of certifying algorithms, which provide a computer-verifiable certificate of correctness alongside their answer. We show that both approaches are sound and complete, analyze whether they can be generated and verified efficiently, and show how to apply them to concrete planning algorithms. The experimental evaluation shows that verifying optimality comes with a cost but is still practically feasible. Furthermore it confirms that the tested planner configurations provide optimal plans on the given instances, as all certificates were verified successfully

Optimality Certificates for Classical Planning

Algorithms are usually shown to be correct on paper, but bugs in their implementations can still lead to incorrect results. In the case of classical planning, it is fortunately straightforward to check whether a computed plan is correct. For optimal planning, however, plans are additionally required to have minimal cost, which is significantly more difficult to verify. While some domain-specific approaches exists, we lack a general tool to verify optimality for arbitrary problems. We bridge this gap and introduce two approaches based on the principle of certifying algorithms, which provide a computer-verifiable certificate of correctness alongside their answer. We show that both approaches are sound and complete, analyze whether they can be generated and verified efficiently, and show how to apply them to concrete planning algorithms. The experimental evaluation shows that verifying optimality comes with a cost, but is still practically feasible. Furthermore, it confirms that the tested planner configurations provide optimal plans on the given instances, as all certificates were verified successfully

Zero-Knowledge Proofs for Classical Planning Problems

In classical planning, the aim is to find a sequence of deterministic actions leading from the initial to a goal state. In this work, we consider the scenario where a party who knows the solution to a planning task, called the prover, wants to convince a second party, the verifier, that it has the solution without revealing any information about the solution itself. This is relevant in domains where privacy is important, for example when plans contain sensitive information or when the solution should not be revealed upfront. We achieve this by introducing a zero-knowledge protocol for plan existence. By restricting ourselves to tasks with polynomially-bounded plan length, we are able to construct a protocol that can be run efficiently by both the prover and verifier. The resulting protocol does not rely on any reduction, has a constant number of rounds, and runs in time polynomial in the size of the task

A novel in silico method to quantify primary stability of screws in trabecular bone

Insufficient primary stability of screws in bone leads to screw loosening and failure. Unlike conventional continuum finite-element models, micro-CT based finite-element analysis (micro-FE) is capable of capturing the patient-specific bone micro-architecture, providing accurate estimates of bone stiffness. However, such in silico models for screws in bone highly overestimate the apparent stiffness. We hypothesized that a more accurate prediction of primary implant stability of screws in bone is possible by considering insertion-related bone damage. We assessed two different screw types and loading scenarios in 20 trabecular bone specimens extracted from 12 cadaveric human femoral heads (N = 5 for each case). In the micro-FE model, we predicted specimen-specific Young's moduli of the peri-implant bone damage region based on morphometric parameters such that the apparent stiffness of each in silico model matched the experimentally measured stiffness of the corresponding in vitro specimen as closely as possible. The standard micro-FE models assuming perfectly intact peri-implant bone overestimated the stiffness by over 330%. The consideration of insertion related damaged peri-implant bone corrected the mean absolute percentage error down to 11.4% for both loading scenarios and screw types. Cross-validation revealed a mean absolute percentage error of 14.2%. We present the validation of a novel micro-FE modeling technique to quantify the apparent stiffness of screws in trabecular bone. While the standard micro-FE model overestimated the bone-implant stiffness, the consideration of insertion-related bone damage was crucial for an accurate stiffness prediction. This approach provides an important step toward more accurate specimen-specific micro-FE models. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2415-2424, 2017.status: publishe

Chemical constituents from Waltheria indica exert in vitro activity against Trypanosoma brucei and T. cruzi

Six extracts from the roots and the aerial parts of Waltheria indica L. (Malvaceae) were screened for their in vitro antitrypanosomal activity towards Trypanosoma brucei brucei STIB 427 strain, T. brucei rhodesiense STIB 900 and Trypanosoma cruzi Tulahuen C4. The dichloromethane extract from the roots showed the highest activity against T. cruzi (IC50=0.74 μg/mL) as well as a good selectivity index (SI value of 35). Based on these results, this extract was fractionated and led to the isolation of three alkaloids (adouetin X (1), waltheriones A (2) and C (3)) and three pentacyclic triterpene derivatives (betulinic acid (4), 3β-acetoxy-27-trans-caffeoyloxyolean-12-en-28-oic acid methyl ester (5) and 3β-acetoxy-27-cis-caffeoyloxyolean-12-en-28-oic acid methyl ester (6)) identified by 1D and 2D NMR, UV, IR and MS analyses. Among these, waltherione C exhibited the highest and selective antitrypanosomal activity towards T. cruzi (IC50=1.93 μM) with low cytotoxicity (IC50=101.23 μM), resulting in a selectivity index value of 52. Waltherione C conforms to hit activity criteria with respect to T. cruzi as required by the WHO/TDR

Antitrypanosomal quinoline alkaloids from the roots of Waltheria indica

Chemical investigation of the dichloromethane root extract of Waltheria indica led to the isolation and characterization of 10 quinoline alkaloids, namely, 8-deoxoantidesmone (1), waltheriones E-L (2-9), and antidesmone (10). Among these, compounds 2-9 have not yet been described in the literature. Their chemical structures were established by means of spectroscopic data interpretation including (1)H and (13)C NMR, HSQC, HMBC, COSY, and NOESY experiments and UV, IR, and HRESIMS. The absolute configurations of the compounds were established by comparison of experimental and TDDFT-calculated ECD spectra. In addition, the isolated constituents were evaluated for their in vitro antitrypanosomal activity. Compounds 4, 5, and 8 showed potent and selective growth inhibition toward Trypanosoma cruzi with IC50 values between 0.02 and 0.04 μM. Cytotoxicity for mouse skeletal L-6 cells was also determined for these compounds

Antitrypanosomal Quinoline Alkaloids from the Roots of <i>Waltheria indica</i>

Chemical investigation of the dichloromethane root extract of <i>Waltheria indica</i> led to the isolation and characterization of 10 quinoline alkaloids, namely, 8-deoxoantidesmone (<b>1</b>), waltheriones E–L (<b>2</b>–<b>9</b>), and antidesmone (<b>10</b>). Among these, compounds <b>2</b>–<b>9</b> have not yet been described in the literature. Their chemical structures were established by means of spectroscopic data interpretation including ¹H and ¹³C NMR, HSQC, HMBC, COSY, and NOESY experiments and UV, IR, and HRESIMS. The absolute configurations of the compounds were established by comparison of experimental and TDDFT-calculated ECD spectra. In addition, the isolated constituents were evaluated for their in vitro antitrypanosomal activity. Compounds <b>4</b>, <b>5</b>, and <b>8</b> showed potent and selective growth inhibition toward <i>Trypanosoma cruzi</i> with IC₅₀ values between 0.02 and 0.04 μM. Cytotoxicity for mouse skeletal L-6 cells was also determined for these compounds