bluuebunny/crossref_metadata_2025 huggingface dataset:
Circulating Pentraxin-3 and its association with C-reactive protein levels and disease activity in patients with chronic spontaneous urticaria
Authors: Beyaz Şengül , Belkaya Serkan , Öztop Nida
Published: July 2023

Introduction: Pentraxin-3 (PTX3) is a soluble long pentraxin molecule that regulates inflammatory responses. This study aimed to determine the plasma levels of plasma PTX-3 as an inflammation marker in chronic spontaneous urticaria (CSU) and whether the PTX3 levels correlate with disease activity and other clinical parameters, including acute phase reactants and biomarkers.
Methods: The study included 70 CSU patients and 30 healthy controls. Plasma PTX3 levels were measured by ELISA. CSU disease activity was evaluated with the urticaria activity score summed over 7 days. Complete blood count, C-reactive protein (CRP), transaminases, total IgE, antinuclear antibody, anti-thyroid peroxidase, anti-thyroglobulin, and D-dimer levels were recorded.
Results: Of the 70 patients, 52 (74.3%) were female, with a mean age of 37.51 ± 11.80 years. Disease activity was severe in 43, moderate in 15, and mild in 12 patients. Mean PTX3 levels were elevated in CSU patients compared to healthy controls (0.81 vs. 0.55 ng/mL, p = 0.031). The mean CRP levels were higher in patients than in the controls (4.26 vs. 1.57 mg/L, p = 0.023). Patients also had higher D-dimer levels than the controls (5.96 vs. 0.59 mg/L, p < 0.001). A significant positive correlation was found between PTX3 and CRP levels (r = 0.508, p < 0.001) and between D-dimer levels and UAS7 (r = 0.338, p = 0.004) and CRP (r = 0.213, p = 0.034) levels. A multivariable stepwise regression analysis showed that the one-unit increase in the CRP level increased to 38.19 units in the PTX3 level (95% confidence interval [17.40–58.98], p < 0.001).
Conclusion: Circulating levels of CRP and PTX3, two members of the pentraxin family, are significantly correlated and elevated in CSU patients with increasing disease activity, indicating their utility as inflammatory markers in CSU.
\(\textit{In vitro}\) regeneration of \(\textit{Renanthera imschootiana}\) Rolfe from protocorm-like body
Authors: Nie Bing H’Yon , Thai Vinh Tran , Kim Cong Vu , Thi Tham Dang , Duy Nong Van
Published: July 2023

Renanthera imschootiana Rolfe is an extremely rare and endangered tropical epiphytic orchid. Studies on in vitro culture of R. imschootiana were conducted in order to conserve and increase the genetic pool of this wild orchid species. In this study, the effect of plant growth regulators (BA and NAA), ripe bananas in combination with potato, humic acid, and silver nanoparticles (AgNPs) were investigated to find a suitable condition for in vitro plant regeneration from R. imschootiana protocorm-like body (PLB). The results showed that after 45 days of culture, MS medium supplemented with 100 g ripe banana/liter and 100 g potato/liter was suitable for regenerating shoots from the protocorm-like body (PLB) (17.56 shoots/PLBs and 100.00% of shoot-regenerating PLBs); MS medium supplemented with 2.0 mg/L BA, 0.3 mg/L NAA and 4 ppm AgNPs was the most suitable for the growth of shoots after 60 days of culture (10.00 leaves/shoot and shoot length of 4.22 cm). The in vitro shoots were transferred to half-strength MS supplemented with humic acid and AgNPs to investigate the root formation of R. imschootiana. After 60 days of culture, the best rooting was obtained at 2.0 mg/L humic acid and 6 ppm AgNPs (8.33 roots/shoot; root length of 4.00 cm and 100.00% root formation). The findings suggest that the in vitro micropropagation from R. imschootiana protocorm-like body provides a useful alternative tool for the conservation of this endangered species.
Characterization of chalcone isomerase 4A \(\textit{(CHI4A)}\) gene in \(\textit{Pueraria mirifica}\)
Authors: Thu Thuy Cao Thi , Bich Ngoc Nguyen Thi , Kieu Oanh Pham Thi , Thu Dung Cao Thi , Thu Hue Huynh Thi
Published: July 2023

Pueraria mirifica is a popular medicinal plant and is rich in phytoestrogens, especially isoflavonoids. The chalcone isomerase (CHI) gene is well-known as a key factor in biosynthetic pathways such as flavonoid, isoflavonoid, and anthocyanin biosynthesis. Among four CHI subfamilies, group IV remained largely uncharacterized in P. mirifica. By isolation and gene cloning, the CHI4A gene was amplified and sequenced. A dataset that included CHI4A genes from isolation, transcriptome, and Glycine max CHI4A was constructed for analysis. A total of 31 single nucleotide polymorphism (SNPs) was detected among sequences and 14 SNPs were found in P. mirifica subgroups. Thirteen SNPs changed the amino acid sequences of CHI4A genes; however, they do not affect core active residues in the protein structure. Two active sites typical for group 4 CHI in the Fabaceae family: Ile50 and Tyr106; and one conserved site Asn113, were found in this study, which is similar to the result of the previous study on CHI4. A three-dimensional protein model of isolated P. mirifica CHI4A enzyme was constructed with a high confidence level. The result provides more information about the variation and protein profile of the CHI4A gene for further experiments.
Pola Asuh Orang Tua Dalam Mengatasi Perilaku Sibling Rivarly Pada Anak Usia Dini
Authors: Ulkhatiata Id’ha Tutfi , Diana Raden Rachmy
Published: July 2023

Sibling rivarly is a competitive behavior between siblings that can cause jealousy in children, in overcoming it, parents must have basic knowledge about this behavior, so this study aims to describe how parents' pola asuhes in dealing with sibling rivarly behavior. This research is a type of qualitative-descriptive research based on post-positivism philosophy, with research subjects of three families having two or more children with an age limit of 0-6 years. Based on the results of this study, of the 3 subjects, there were 2 families who had the same handling strategy, namely from the start they had instilled knowledge to always get along with fellow siblings, to be fair, not to compare children but there was also one subject that needed to be improved in using pola asuhes to deal with behavior sibling rivarly.
Penerapan Program Celengan Kayu dalam Upaya Meningkatkan Karakter Hemat pada Anak Raudatul Athfal
Authors: Risalah Ainur , Alistiana Alisa , Pangastuti Ratna , Taseman Taseman , Safarudin Safarudin
Published: July 2023

This study aims to describe: (1) implementation of the children's wooden piggy bank program, (2) Obstacles faced and, (3) Suggested solutions This research is qualitative in nature with strategic case studies. The research location is Raudhatul Athfal (RA) Al Ghozali Porong Sidoarjo. Research subjects; Children, Principals, Teachers, and Parents. Collecting research data by means of; observations, interviews, documents, and audiovisual materials. After the data has been collected, data analysis is carried out by means of data condensation, data display, and conclusions drawing. The results of the study: (1) The application of the wooden piggy bank program is carried out every 15 (fifteen) first minutes of class entry or during recess. The wooden piggy bank program is a program to strengthen the character of independence, especially the character of frugal living (2) Constraints faced; there are economic limitations so that no one brings money, lack of awareness and knowledge of parents to routinely carry money that will run out (4) Solutions; teachers need support and patience to create a pleasant saving atmosphere, parents need support to regularly bring money to save according to ability
Formulación matemática y evaluación de la actividad antihipertensiva de yogurt griego elaborado con fines preventivos a las enfermedades dinamizadas por COVID19
Authors: Mares-Mares Everardo , García-de-la-Rosa Luis Armando , Acosta-Castillo María Guadalupe de Lourdes
Published: July 2023

Dentro de las estrategias de la inmuno-nutrición para prevenir y/o combatir los problemas causados por el COVID-19, se ha descrito que los péptidos bioactivos de alimentos ricos en proteína y de alta calidad nutrimental como el yogurt, poseen efectos positivos directos e indirectos en el sistema inmune. Más aún, durante la pandemia se ha reportado que los péptidos con potencial inhibitorio de la Enzima Convertidora de Angiotensina (IECA) derivados de productos lácteos participan en la regulación y/o bloqueo de los mecanismos quimio-enzimáticos de las patogenias como la hipertensión. Por lo tanto, el estudio in vitro sobre efecto de los péptidos bioactivos de alimentos sobre mecanismos moleculares de las enfermedades dinamizadas por el virus SARS-CoV-2 permitirá integrar un cuadro terapéutico molecular preventivo que determine parcialmente el potencial inmune de un alimento. En este proyecto se busca optimizar una fórmula de yogurt griego mediante la metodología estadística de un diseño superficie de respuesta y evaluación sensorial incluyendo ingredientes como el complejo B, vitamina C e inulina. Posteriormente, se realizarán las determinaciones del análisis químico proximal para la declaración nutrimental de acuerdo con la NOM-051-SCFI/SSA1-2010. El yogurt griego se someterá a un modelo in vitro de simulación salivar-gástrica-intestinal para la liberación de péptidos bioactivos y serán sometidos a diferentes concentraciones al análisis in vitro de la actividad inhibitoria de la ECA (ensayo de actividad antihipertensiva). Con los resultados obtenidos se obtendrá la IC50. Finalmente, se podrá proyectar y constatar las hipótesis sobre los beneficios hacia la salud de los péptidos bioactivos del yogurt griego para su consideración futura como alimento funcional).
Contemporary Interpretations of Ophthalmological Manifestations of Chronic Myeloproliferative Neoplasms
Authors: Moshetova Larisa K. , Egoryan Lidia B. , Vinogradova Olga J. , Turkina Ksenia I. , Shikhbabaeva Dgariat I.
Published: July 2023

The course of chronic myeloproliferative neoplasms (CMPN), a group of systemic hematological diseases, can be accompanied by various complications and changes in tissues and organs of the whole organism. The eye is the only organ where damage of nerve fibers and blood vessels can be directly observed and examined, and ocular symptoms can be the initial, manifest of systemic pathology, the toxic effects of modern targeted therapy, or the first manifestation of a relapse of the disease after treatment. The most frequently described manifestations are caused by hematological anomalies that cause microvascular disorders. Such changes today remain insufficiently studied in terms of the using new research methods and contemporary targeted therapy. In addition, ocular symptoms may precede more serious extraocular complications. Combined ophthalmological and hematological examination of patients with CMPN can become a preventive approach for early diagnosis and timely treatment.
Planning for Temporally Extended Goals in Pure-Past Linear Temporal Logic
Authors: Bonassi Luigi , De Giacomo Giuseppe , Favorito Marco , Fuggitti Francesco , Gerevini Alfonso Emilio , Scala Enrico
Published: July 2023

We study classical planning for temporally extended goals expressed in Pure-Past Linear Temporal Logic (PPLTL).
PPLTL is as expressive as Linear-time Temporal Logic on finite traces (LTLf), but as shown in this paper, it is computationally much better behaved for planning.
Specifically, we show that planning for PPLTL goals can be encoded into classical planning with minimal overhead, introducing only a number of new fluents that is at most linear in the PPLTL goal and no spurious additional actions.
Based on these results, we implemented a system called Plan4Past, which can be used along with state-of-the-art classical planners, such as LAMA.
An empirical analysis demonstrates the practical effectiveness of Plan4Past, showing that a classical planner generally performs better with our compilation than with other existing compilations for LTLf goals over the considered benchmarks.
Deadline-Aware Multi-Agent Tour Planning
Authors: Huang Taoan , Shivashankar Vikas , Caldara Michael , Durham Joseph , Li Jiaoyang , Dilkina Bistra , Koenig Sven
Published: July 2023

The increasing demand for same-day delivery and the commitment of e-commerce companies to this service raise a number of challenges in logistics. One of these challenges for fulfillment centers is to coordinate hundreds of mobile robots in their automated warehouses efficiently to allow for the retrieval and packing of thousands of ordered items within the promised delivery deadlines. We formulate this challenge as the new problem of deadline-aware multi-agent tour planning, where the objective is to coordinate robots to visit multiple picking stations in congested warehouses to allow as many orders to be packed on time as possible. To solve it, we propose LaRge NeighbOrhood Search for DEadline-Aware MulTi-Agent Tour PlAnning (ROSETTA). We conduct extensive experiments to evaluate ROSETTA with up to 350 robots in simulated warehouses inspired by KIVA systems. We show that it increases the number of orders completed on time by up to 38% compared to several baseline algorithms and also significantly outperforms them in terms of throughput and station utilization.
Computing Domain Abstractions for Optimal Classical Planning with Counterexample-Guided Abstraction Refinement
Authors: Kreft Raphael , Büchner Clemens , Sievers Silvan , Helmert Malte
Published: July 2023

Abstraction heuristics are the state of the art in optimal classical
planning as heuristic search. A popular method for computing
abstractions is the counterexample-guided abstraction refinement
(CEGAR) principle, which has successfully been used for projections,
which are the abstractions underlying pattern databases, and
Cartesian abstractions. While projections are simple and fast to
compute, Cartesian abstractions subsume projections and hence allow
more fine-grained abstractions, however at the expense of efficiency.
Domain abstractions are a third class of abstractions between
projections and Cartesian abstractions in terms of generality. Yet,
to the best of our knowledge, they are only briefly considered in the
planning literature but have not been used for computing heuristics
yet. We aim to close this gap and compute domain abstractions by using
the CEGAR principle. Our empirical results show that domain
abstractions compare favorably against projections and Cartesian
abstractions.
Exact Anytime Multi-Agent Path Finding Using Branch-and-Cut-and-Price and Large Neighborhood Search
Authors: Lam Edward , Harabor Daniel D. , Stuckey Peter J. , Li Jiaoyang
Published: July 2023

Given a set of agents on a grid, the multi-agent path finding problem aims to find a path that moves each agent from its given start location to its target location such that they do not collide and that the sum of arrival times is minimized. LNS2 is a state-of-the-art algorithm for anytime, suboptimal solving. It is an upper-bounding algorithm that repeatedly adjusts an existing solution and, being a local search, is oblivious to optimality. BCP is a state-of-the-art algorithm for exact solving. It is a lower-bounding tree search that attempts to tighten the lower bound until a solution appears. As BCP operates on the lower bound, the first solution it finds is optimal or nearly optimal, and therefore has poor anytime behavior. This paper proposes to tightly couple LNS2 and BCP to achieve better anytime, suboptimal solving while retaining the optimality guarantee of BCP. Experiments indicate that the combination achieves better anytime behavior than BCP in general and better suboptimal performance than LNS2 on congested maps.
Efficient Reasoning about Infeasible One Machine Sequencing
Authors: Mencía Raúl , Mencía Carlos , Marques-Silva Joao
Published: July 2023

This paper addresses the tasks of explaining and correcting infeasible one machine sequencing problems with a limit on the makespan. Concretely, the paper studies the computation of high-level explanations and corrections, which are given in terms of irreducible subsets of the set of jobs. To achieve these goals, the paper shows that both tasks can be reduced to the general framework of computing a minimal set over a monotone predicate (MSMP). The reductions enable the use of any general-purpose algorithm for solving MSMP, and three well-known approaches are instantiated for the two tasks. Furthermore, the paper details efficient scheduling techniques aimed at enhancing the performance of the proposed algorithms. The experimental results confirm that the proposed approaches are efficient in practice, and that the scheduling optimizations enable critical performance gains.
A Column Generation Approach to Correlated Simple Temporal Networks
Authors: Murray Andrew , Arulselvan Ashwin , Cashmore Michael , Roper Marc , Frank Jeremy
Published: July 2023

Probabilistic Simple Temporal Networks (PSTN) represent scheduling problems under temporal uncertainty. Strong controllability (SC) of PSTNs involves finding a schedule to a PSTN that maximises the probability that all constraints are satisfied (robustness). Previous approaches to this problem assume independence of probabilistic durations, and approximate the risk by bounding it above using Boole’s inequality. This gives no guarantee of finding the schedule optimising robustness, and fails to consider correlations between probabilistic durations that frequently arise in practical applications. In this paper, we formally define the Correlated Simple Temporal Network (Corr-STN) which generalises the PSTN by removing the restriction of independence. We show that the problem of Corr-STN SC is convex for a large class of multivariate (log-concave) distributions. We then introduce an algorithm capable of finding optimal SC schedules to Corr-STNs, using the column generation method. Finally, we validate our approach on a number of Corr-STNs and find that our method offers more robust solutions when compared with prior approaches.
The Small Solution Hypothesis for MAPF on Strongly Connected Directed Graphs Is True
Authors: Nebel Bernhard
Published: July 2023

The determination of the computational complexity of multi-agent pathfinding on directed graphs (diMAPF) has been an open research problem for many years. While diMAPF has been shown to be polynomial for some special cases, only recently, it has been established that the problem is NP-hard in general. Further, it has been proved that diMAPF will be in NP if the short solution hypothesis for strongly connected directed graphs holds. In this paper, it is shown that this hypothesis is indeed true, even when one allows for synchronous rotations.
Beyond Pairwise Reasoning in Multi-Agent Path Finding
Authors: Shen Bojie , Chen Zhe , Li Jiaoyang , Cheema Muhammad Aamir , Harabor Daniel D. , Stuckey Peter J.
Published: July 2023

In Multi-Agent Path Finding (MAPF), we are asked to plan collision-free paths for teams of moving agents. Among the leading methods for optimal MAPF is Conflict-Based Search (CBS), an algorithmic family which has received intense attention in recent years and for which large advancements in efficiency and effectiveness have been reported. Yet all of the recent CBS gains come from reasoning over pairs of agents only. In this paper, we show how to further improve CBS by reasoning about more than two agents at the same time. Our new cluster reasoning techniques allow us to generate stronger bounds for CBS and to identify more bypasses (alternative cost-equivalent paths), which reduce the number of nodes in the CBS conflict tree.
Symmetry Detection and Breaking in Linear Cost-Optimal Numeric Planning
Authors: Shleyfman Alexander , Kuroiwa Ryo , Beck J. Christopher
Published: July 2023

One of the main challenges of domain-independent numeric planning is the complexity of the search problem. The exploitation of structural symmetries in a search problem can constitute an effective method of pruning search branches that may lead to exponential improvements in performance. For over a decade, symmetry breaking techniques have been successfully used within both optimal and satisficing classical planning. In this work, we show that symmetry detection methods applied in classical planning with some effort can be modified to detect symmetries in linear numeric planning. The detected symmetry group, thereafter, can be used almost directly in the A*-based symmetry breaking algorithms such as DKS and Orbit Space Search. We empirically validate that symmetry pruning can yield a substantial reduction in the search effort, even if algorithms are equipped with a strong heuristic, such as LM-cut.
Adaptation and Communication in Human-Robot Teaming to Handle Discrepancies in Agents’ Beliefs about Plans
Authors: Zhang Yuening , Williams Brian
Published: July 2023

When agents collaborate on a task, it is important that they have some shared mental model of the task routines -- the set of feasible plans towards achieving the goals. However, in reality, situations often arise that such a shared mental model cannot be guaranteed, such as in ad-hoc teams where agents may follow different conventions or when contingent constraints arise that only some agents are aware of. Previous work on human-robot teaming has assumed that the team has a set of shared routines, which breaks down in these situations. In this work, we leverage epistemic logic to enable agents to understand the discrepancy in each other's beliefs about feasible plans and dynamically plan their actions to adapt or communicate to resolve the discrepancy. We propose a formalism that extends conditional doxastic logic to describe knowledge bases in order to explicitly represent agents' nested beliefs on the feasible plans and state of execution. We provide an online execution algorithm based on Monte Carlo Tree Search for the agent to plan its action, including communication actions to explain the feasibility of plans, announce intent, and ask questions. Finally, we evaluate the success rate and scalability of the algorithm and show that our agent is better equipped to work in teams without the guarantee of a shared mental model.
Dynamic Weight Setting for Personnel Scheduling with Many Objectives
Authors: Kletzander Lucas , Musliu Nysret
Published: July 2023

When large sets of constraints and objectives are combined in a practical optimization problem, managing all these potentially conflicting goals can become very difficult and might require to solve an instance multiple times. First, an instance might be infeasible with the current constraints, in which case our system introduces a novel violation score to help identify the constraints that need to be relaxed for the next run. Second, multiple objectives are often combined using a linear combination with hand-crafted weights, which are very difficult to set such that the result matches the expectations regarding the balance between individual objectives. Instead, the user can tell our system particular thresholds for the expected changes in objectives, e.g., to reduce objective 1 by 10 % while not increasing objective 2 by more than 5 %. Dynamic weight setting automatically adapts the weights to reach these thresholds or uses the violation scores to explain reasons for not reaching thresholds. It can not only be used for soft constraints, but also to determine weights when hard constraints are internally represented as soft constraints in meta-heuristics. While the methodology is general, we have implemented it in the context of a personnel scheduling framework of our industry partner and present a detailed evaluation on the domain of Bus Driver Scheduling, where its benefits can be seen in multiple scenarios.
Combining Clinical and Spatial Constraints into Temporal Planning to Personalize Physical Rehabilitation
Authors: Umbrico Alessandro , Benadduci Marco , Bevilacqua Roberta , Cesta Amedeo , Fracasso Francesca , Maranesi Elvira , Orlandini Andrea , Cortellessa Gabriella
Published: July 2023

This work investigate temporal planning to synthesize personalized physical rehabilitation programs. The first contribution of the work concerns the representation of (heterogeneous) clinical and spatial constraints into a planning framework. The second contribution is the integration of numerical and symbolic reasoning to synthesize technically valid and coherent plans with respect to different clinical objectives. The experimental section discusses the developed planner from a technical view, assessing solving and personalization capabilities, and from a clinical view, assessing the efficacy of plans on the involved patients.
Reinforcement Learning for Omega-Regular Specifications on Continuous-Time MDP
Authors: Falah Amin , Guha Shibashis , Trivedi Ashutosh
Published: July 2023

Continuous-time Markov decision processes (CTMDPs) are canonical models to express sequential decision-making under dense-time and stochastic environments. When the stochastic evolution of the environment is only available via sampling, model-free reinforcement learning (RL) is the algorithm-of-choice to compute optimal decision sequence. RL, on the other hand, requires the learning objective to be encoded as scalar reward signals. Since doing such translations manually is both tedious and error-prone, a number of techniques have been proposed to translate high-level objectives (expressed in logic or automata formalism) to scalar rewards for discrete-time Markov decision processes. Unfortunately, no automatic translation exists for CTMDPs.

We consider CTMDP environments against the learning objectives expressed as omega-regular languages. Omega-regular languages generalize regular languages to infinite-horizon specifications and can express properties given in popular linear-time logic LTL. To accommodate the dense-time nature of CTMDPs, we consider two different semantics of omega-regular objectives: 1) satisfaction semantics where the goal of the learner is to maximize the probability of spending positive time in the good states, and 2) expectation semantics where the goal of the learner is to optimize the long-run expected average time spent in the ''good states'' of the automaton. We present an approach enabling correct translation to scalar reward signals that can be readily used by off-the-shelf RL algorithms for CTMDPs. We demonstrate the effectiveness of the proposed algorithms by evaluating it on some popular CTMDP benchmarks with omega-regular objectives.
Timed Partial Order Inference Algorithm
Authors: Watanabe Kandai , Fainekos Georgios , Hoxha Bardh , Lahijanian Morteza , Prokhorov Danil , Sankaranarayanan Sriram , Yamaguchi Tomoya
Published: July 2023

In this work, we propose the model of timed partial orders (TPOs) for specifying workflow schedules, especially for modeling manufacturing processes. TPOs integrate partial orders over events in a workflow, specifying ``happens-before'' relations, with timing constraints specified using guards and resets on clocks -- an idea borrowed from timed-automata specifications. TPOs naturally allow us to capture event ordering, along with a restricted but useful class of timing relationships. Next, we consider the problem of mining TPO schedules from workflow logs, which include events along with their time stamps. We demonstrate a relationship between formulating TPOs and the graph-coloring problem, and present an algorithm for learning TPOs with correctness guarantees.
We demonstrate our approach on synthetic datasets, including two datasets inspired by real-life applications of aircraft turnaround and gameplay videos of the Overcooked computer game. Our TPO mining algorithm can infer TPOs involving hundreds of events from thousands of data-points within a few seconds. We show that the resulting TPOs provide useful insights into the dependencies and timing constraints for workflows.
Core Expansion in Optimization Crosswords
Authors: Botea Adi , Bulitko Vadim
Published: July 2023

In constraint optimization many problem instances remain challenging to current technology.
We focus on the Romanian Crosswords Competition Problem.
It is a challenging, NP-hard constraint optimization problem
where state-of-the-art AI has been lagging significantly behind top human performance.
We present an approach that first builds a core, a portion of the problem that will
have a high contribution to the objective function.
A core is grown into a seed, a partial solution with
a subset of variables defined and instantiated.
Seeds are further extended into full solutions.
Our approach takes as input the size of a rectangular core to consider,
and the locations of zero or more black cells inside the core.
The results advance state-of-the-art substantially.
We report a boost in the scores obtained, bringing our top solutions
in the vicinity of top human entries.
Fine-Grained Complexity Analysis of Multi-Agent Path Finding on 2D Grids
Authors: Geft Tzvika
Published: July 2023

Multi-Agent Path Finding (MAPF) is a fundamental motion coordination problem arising in multi-agent systems with a wide range of applications.
The problem's intractability has led to extensive research on improving the scalability of solvers for it.
Since optimal solvers can struggle to scale, a major challenge that arises is understanding what makes MAPF hard.
We tackle this challenge through a fine-grained complexity analysis of time-optimal MAPF on 2D grids, thereby closing two gaps and identifying a new tractability frontier.
First, we show that 2-colored MAPF, i.e., where the agents are divided into two teams, each with its own set of targets, remains NP-hard.
Second, for the flowtime objective (also called sum-of-costs), we show that it remains NP-hard to find a solution in which agents have an individually optimal cost, which we call an individually optimal solution.
The previously tightest results for these MAPF variants are for (non-grid) planar graphs.
We use a single hardness construction that replaces, strengthens, and unifies previous proofs.
We believe that it is also simpler than previous proofs for the planar case as it employs minimal gadgets that enable its full visualization in one figure.
Finally, for the flowtime objective, we establish a tractability frontier based on the number of directions agents can move in.
Namely, we complement our hardness result, which holds for three directions, with an efficient algorithm for finding an individually optimal solution if only two directions are allowed.
This result sheds new light on the structure of optimal solutions, which may help guide algorithm design for the general problem.
Towards Effective Multi-Valued Heuristics for Bi-objective Shortest-Path Algorithms via Differential Heuristics
Authors: Zhang Han , Salzman Oren , Felner Ariel , Kumar T. K. Satish , Skyler Shawn , Hernández Ulloa Carlos , Koenig Sven
Published: July 2023

In bi-objective graph search, each edge is annotated with a cost pair, where each cost corresponds to an objective to optimize. We are interested in finding all undominated paths from a given start state to a given goal state (called the Pareto front). Almost all existing works of bi-objective search use single-valued heuristics, which use one number for each objective, to estimate the cost between any given state and the goal state. However, single-valued heuristics cannot reflect the trade-offs between the two costs. On the other hand, multi-valued heuristics use a set of pairs to estimate the Pareto front between any given state and the goal state and are more informed than single-valued heuristics. However, they are rarely studied and have yet to be investigated in explicit state spaces by any existing work. In this paper, we are interested in using multi-valued heuristics to improve bi-objective search algorithms in explicit state spaces. More specifically, we generalize Differential Heuristics (DHs), a class of memory-based heuristics for single-objective search, to bi-objective search, resulting in Bi-objective Differential Heuristics (BO-DHs). We propose several techniques to reduce the memory usage and computational overhead of BO-DHs significantly. Our experimental results show that, with suggested improvement and tuned parameters, BO-DHs can reduce the node expansion and runtime of a bi-objective search algorithm by up to an order of magnitude, paving the way for more effective multi-valued heuristics.
Efficient Multi Agent Path Finding with Turn Actions
Authors: Zhang Yue , Harabor Daniel , Le Bodic Pierre , Stuckey Peter J.
Published: July 2023

Current approaches for real-world Multi-Agent Path Finding (MAPF) usually start with a simplified MAPF model and modify the resulting plans so they are kinematically feasible. We investigate one such problem, called MAPF with turn actions MAPF_T, and show that ignoring the kinematic constraints significantly increases solution cost. A first modification of the popular Conflict-Based Search algorithm to MAPF_T yields significantly better plans but comes at the cost of substantial decreases in scalability. We then introduce several techniques that can improve the performance of CBS for MAPF_T, including stronger and generalised versions of existing symmetry-breaking constraints and a novel pruning technique that eliminates redundant branches in the CBS constraint tree. Experimental results on six popular MAPF domains show convincing improvements for CBS success rate and substantial reductions in node expansions and runtime.
Novelty and Lifted Helpful Actions in Generalized Planning
Authors: Lei Chao , Lipovetzky Nir , Ehinger Krista A.
Published: July 2023

It has been shown recently that successful techniques in classical planning, such as goal-oriented heuristics and landmarks, can improve the ability to compute planning programs for generalized planning (GP) problems. In this work, we introduce the notion of action novelty rank, which computes novelty with respect to a planning program, and propose novelty-based generalized planning solvers, which prune a newly generated planning program if its most frequent action repetition is greater than a given bound v, implemented by novelty-based best-first search BFS(v) and its progressive variant PGP(v). Besides, we introduce lifted helpful actions in GP derived from action schemes, and propose new evaluation functions and structural program restrictions to scale up the search. Our experiments show that the new algorithms BFS(v) and PGP(v) outperform the state-of-the-art in GP over the standard generalized planning benchmarks. Practical findings on the above-mentioned methods in generalized planning are briefly discussed.
GePA*SE: Generalized Edge-Based Parallel A* for Slow Evaluations
Authors: Mukherjee Shohin , Likhachev Maxim
Published: July 2023

Parallel search algorithms have been shown to improve planning speed by harnessing the multithreading capability of modern processors. One such algorithm PA*SE achieves this by parallelizing state expansions, whereas another algorithm ePA*SE achieves this by effectively parallelizing edge evaluations. ePA*SE targets domains in which the action space comprises actions with expensive but similar evaluation times. However, in a number of robotics domains, the action space is heterogenous in the computational effort required to evaluate the cost of an action and its outcome. Motivated by this, we introduce GePA*SE: Generalized Edge-based Parallel A* for Slow Evaluations, which generalizes the key ideas of PA*SE and ePA*SE, i.e., parallelization of state expansions and edge evaluations, respectively. This extends its applicability to domains that have actions requiring varying computational effort to evaluate them. The open-source code for GePA*SE, along with the baselines, is available here:
https://github.com/shohinm/parallel_search
A-ePA*SE: Anytime Edge-Based Parallel A* for Slow Evaluations
Authors: Yang Hanlan , Mukherjee Shohin , Likhachev Maxim
Published: July 2023

Anytime search algorithms are useful for planning problems where a solution is desired under a limited time budget. Anytime algorithms first aim to provide a feasible solution quickly and then attempt to improve it until the time budget expires. On the other hand, parallel search algorithms utilize the multithreading capability of modern processors to speed up the search. One such algorithm, ePA*SE (Edge-Based Parallel A* for Slow Evaluations), parallelizes edge evaluations to achieve faster planning and is especially useful in domains with expensive-to-compute edges. In this work, we propose an extension that brings the anytime property to ePA*SE, resulting in A-ePA*SE. We evaluate A-ePA*SE experimentally and show that it is significantly more efficient than other anytime search methods. The open-source code for A-ePA*SE, along with the baselines, is available here:
https://github.com/shohinm/parallel_search
Hybrid Search with Graph Neural Networks for Constraint-Based Navigation Planning [Extended Abstract]
Authors: Coupvent des Graviers Marc-Emmanuel , Osanlou Kevin , Guettier Christophe , Cazenave Tristan
Published: July 2023

Route planning for autonomous vehicles is a challenging task, especially in dense road networks with multiple delivery points. Additional external constraints can quickly add overhead to this already-difficult problem that often requires prompt, on-the-fly decisions. This work introduces a hybrid method combining machine learning and Constraint Programming (CP) to improve search performance. A new message passing-based graph neural network tailored to constraint solving and global search is defined. Once trained, a single neural network inference is enough to guide CP search while ensuring solution optimality. Large-scale experiments using real road networks from cities worldwide are presented. The hybrid method is effective in solving complex routing problems, addressing larger problems than those used for model training.
A Fast Rescheduling Algorithm for Real-Time Multi-Robot Coordination [Extended Abstract]
Authors: Paul Adittyo , Feng Ying , Li Jiaoyang
Published: July 2023

One area of research in Multi-Agent Path Finding (MAPF) is to determine how re-planning can be efficiently achieved in the case of the delay of an agent. One option is to determine a new wait ordering to find the most optimal new solution that can be produced by re-ordering the wait order. We propose to use an Edge-Switchable Temporal Plan Graph and an augmented A* algorithm, called Switchable-Edge Search, to approach finding a new optimal wait order. While this is a work in progress still, we have discovered several optimizations for this algorithm, and the results show promising increases in efficiency for the algorithm. We have analyzed our present efficiency in a variety of conditions by measuring re-planning speed in different maps, with varying numbers of agents and randomized scenarios for agents' start and goal locations. We hope that, as we proceed with optimization, we can show that such an approach can be more efficient in practice and be used instead of re-running MAPF to perform cheap re-planning in such situations.
Domain Specific Situated Planning (Student Abstract)
Authors: Thomas Devin Wild
Published: July 2023

Traditionally when planning we assume that we receive the problem instance as input, then formulate a plan, then the clock begins and the agent executes the plan. Sometimes we are forced to consider time passing as we plan, which is known as situated planning. In my dissertation I explore situated planning in three domains: grid based path planning, the orienteering problem and opportunistic science.
111 N HYDRAZINE BIPROPELLANT ENGINE (HBE) WITH GAS-GAS INJECTION
Authors: Boenish Hans , Garcia Carlos , Venkatesh Prashanth Bangalore , Costello Jack , Daniel Evan , Fitzpatrick Michael , Foster Curtis , Graybill Benjamin , Hollinbeck Mesa , Kolano Daniel , Lea Margaret , Osborne Lars , Riley Patrick , Smith Tucker , Barnes Daudi
Published: July 2023

A thruster, designated LE111, utilizes hydrazine and MON3 as fuel and oxidizer and produces a thrust of 111 N at nominal operating conditions with an Isp of up to 328 s. The thruster is throttleable through the use of separate fuel and oxidizer metering valves and is able to transition to a hydrazine monopropellant mode at any point during its operation. Completed qualification testing has demonstrated a versatile operating box that includes chamber pressure-mixture ratio excursions, heated propellants up to 341 K,
and gaseous helium ingestion through propellant flow paths. Overall, the thruster has achieved 15,455 s of accumulated on-time and a maximum continuous burn time of 6,000 s. The thruster achieves its performance through a novel micro-coaxial gas-gas injection scheme and an innovative regeneratively cooled combustion chamber, which uses the oxidizer as the working fluid. The thruster's capabilities and performance recorded during the completed qualification testing are described, and its design is outlined.
This paper is published with the permission of the authors granted to 3AF – Association Aéronautique et Astronautique de France (www.3AF.fr) organizer of the Space Propulsion International conference.
A Research on Architects’ Comfort Conditions in Working Enviroments
Authors: Yardımcı Yiğit Can
Published: July 2023

Architects have difficult working conditions due to the profession of architecture and they stay in the working environment during intensive working hours. For this reason, it is important to improve the comfort conditions in the working environment for architects to feel physically and psychologically better. The aim of this study is to evaluate the comfort conditions in the working environment of architects working in Bursa. In the literature, the number of studies examining the physical comfort conditions of architects in the work environment is limited. Therefore, this study is important in terms of explaining the comfort conditions of architects in their working environment. In this direction, 203 architects were reached and a questionnaire was used as a data collection method. The questionnaire consists of 2 stages. The first phase includes demographic characteristics and the second phases includes questions about comfort conditions. When the comfort conditions of the architects were examined; it was seen that they were satisfied with the sub-factors of artificial lighting, indoor temperature and natural ventilation adequacy, indoor air quality, absence of bad odors in the working environment, seat ergonomics, equipment adequacy. However, they feel uncomfortable with the several auditory comfort conditions in the work environment. When the correlation between demographic characteristics and comfort conditions in the working environment is examined, the correlation coefficients are in the range of 0-0.20, indicating that demographic characteristics have a very weak or no relationship with comfort conditions in the working environment.
Tüketim mekânlarının ve üçüncü yerlerin analizinde yeni bir kavram ve çerçeve önerisi: “mekânyer”
Authors: YAVAN Nuri , KURTAR ANLI Ceyda
Published: July 2023

Bu çalışma coğrafyanın temel kavramlarından ‘mekân’ ve ‘yer’e ilişkin tartışmalar ışığında, tüketimin ve sosyalleşmenin biraradalığını sağlayan üçüncü yerler ile mikro ölçekteki tüketim mekânlarını “mekânyer” olarak kavramsallaştıran yeni bir nosyon ve çerçeve sunmayı amaçlamaktadır. Bu yeni nosyon ve çerçeve bize iki önemli olanak sunmaktadır. Bunlardan ilki, ekonomik coğrafya içerisinde tüketim mekânlarını öne çıkararak, klasik lokasyonel seçim ve ihtiyaç odaklı analizin ötesine geçen bir tartışma yapmamıza imkân sağlamaktadır. İkincisi ise, coğrafya literatüründe teorik olarak tartışılan ve tanımlanan ‘mekân’ ve ‘yer’ kavramlarının mikro tüketim mekânları ölçeğinde işlemselleştirilmesini sağlayarak daha kapsayıcı ve pratik bir yeni bir kavram ve analiz çerçevesi önerisi ortaya koymaktadır. Önerilen kavram hem hizmet ortamı, üçüncü yer ve ilişkisel üçüncü yer kavramsallaştırmaları üzerinden hem de saha çalışmasından elde edilen verilerin analizi ve farklı bir perspektifle yenilikçi olarak yorumlanması üzerinden geliştirilmiştir. Bu bağlamda önerilen ‘mekânyer’ kavramını tanımlayan özellikler, ayrım (tüketim pratikleri, yaşam tarzı ve kültürel sermaye), ölçek (bilinç-duygu, deneyimsel ve ilişkisel), yerin failliği (yerin serbestliği, yerin gerçekleşmesi ve yerin kimliği) ve ürün (sembolik, toplumsal ve bilişsel) olmak üzere dört bileşenden oluşmaktadır. Sözkonusu kavramın inşası ve geliştirilmesinde birbirinden farklı yapılara ve anlamlara sahip iki tüketim mekânı olan Starbucks ve Simit Sarayı örneklem alanı olarak kullanılmıştır. Çalışma hem nitel hem de nicel yöntemi bir arada içeren tasarıma sahiptir. Her iki mekânda toplam 426 anket yapılmıştır. Aynı zamanda Starbucks ve Simit Sarayında 26 tüketici ve 8 yönetici ile derinlemesine görüşmeler gerçekleştirilmiştir. Bu bağlamda çalışmanın en önemli bulgusu, mikro tüketim mekânlarının özellikle de üçüncü yerlerin sosyalleşmeye odaklı yerler olsalar da aynı zamanda toplumun kültürel ayrımlarını ve deneyimlerini hem ürün hem de mekân üzerinden yeniden üretmekte oldukları yönündedir. Bu nedenle tüketim mekânlarının işlemselleştirilmesinde önerilen ‘mekânyer’ kavramının ve sunduğu çerçevenin özelliklerinin birlikte düşünülmesi ve kullanılması daha kapsamlı ve derin bir analiz imkânı sunmaktadır.
Los usos del saber. Una revisión al pensamiento educativo de Max Stirner en torno a una discusión pedagógica clásica
Authors: Mena Bernal Eduardo Ernesto
Published: July 2023

El saber suele ser visto de dos maneras antitéticas: humanista o pragmática. La consecuencia de ello son dos tipos de educación que se oponen mutuamente en la más cotidiana realidad. Asimismo, se suma el hecho de que hoy en día, gracias a visiones que politizaron el saber (tales como la teoría crítica), su uso educativo se vuelve aún más complejo. No obstante, pensadores como Max Stirner —quien no suele recibir la suficiente atención pedagógica— podría ofrecer ideas que permitan resolver de una manera especial dicho conflicto. A través de su potente texto, El falso principio de nuestra educación o humanismo y realismo, ofrece reflexiones que vale la pena matizar y retomar para el presente escrito. Se afirma, pues, que Max Stirner propuso vías intelectuales y prácticas para hacer un uso del saber que reivindica al individuo en los procesos educativos regidos por los dos usos típicos del saber.
El sentido de la pedagogía y su objeto
Authors: Furlán Malamud Alfredo José , Ochoa Reyes Nidia Eli
Published: July 2023

En vista de las problemáticas nacionales y mundiales que nos aquejan, este texto constituye una reflexión acerca del sentido actual de la Pedagogía y su labor para la consecución de los procesos educativos de los sujetos. Partiendo de una breve consideración de su historia en México y de la falta de claridad sobre su modo de ser en nuestro país, aludimos a la Bildung como un concepto ejemplar que puede auxiliarnos en la ampliación del significado del objeto de estudio de la Pedagogía: la educación. Con base en las tesis de Reinhart Koselleck y Walter Benjamin, el presente artículo se detiene en el contraste entre las palabras Bildung, educación y formación, señalando las cercanías y distancias entre ellas. Si bien existen discrepancias al respecto, se considera que las diversas perspectivas latinoamericanas comparten la intención de hacer de la formación humana el objeto de la disciplina pedagógica y no la mercantilización de la educación, que es una vertiente en boga y una de las principales antagonistas del sentido pedagógico que se busca defender. Finalmente, el texto concluye con la defensa de una idea dialéctica de Pedagogía que cuida y procura los procesos educativos, pero que también se hace por mor de estos.