bluuebunny/crossref_metadata_2025 huggingface dataset:
Better Parameter-Free Anytime Search by Minimizing Time Between Solutions
Authors: Thayer Jordan , Benton J. , Helmert Malte
Published: November 2022

This paper presents a new anytime search algorithm, anytime explicitestimation search (AEES). AEES is an anytime search algorithm which attempts to minimize the time between improvements to its incumbent solution by taking advantage of the differences between solution cost and length. We provide an argument that minimizing the time between solutions is ideal behavior for an anytime search algorithm and show that when actions have differing costs, many state-of-the-art search algorithms, including the search strategy of LAMA11 and anytime nonparametric A*, do not minimize the time between solutions. An empirical evaluation on seven domains shows that AEES often has boththe shortest time between incumbent solutions and the best solution in hand for a wide variety of cutoffs.
Precomputed-Direction Heuristics for Suboptimal Grid-Based Path-finding
Authors: Parra Álvaro , Torralba Álvaro , Linares López Carlos
Published: November 2022

This paper describes BubbleDragon, an entry in the 2012 Grid-based Path-Planning Competition. We aim to solve path-finding problems in the minimum time possible by precomputing paths from states in a region to its frontiers. Experimental results show that suboptimal paths for 1024x1024 grids can be retrieved in less than 1ms on average.
Tree Cache
Authors: Anderson Kenneth
Published: November 2022

This program generates a single search tree, compacts it to reduce memory/disk space, then utilizes it to very quickly generate valid paths in an 8-connected gridworld. This technique is similar in principle to RRTs used in robotics.
Subdimensional Expansion and Optimal Task Reassignment
Authors: Wagner Glenn , Choset Howie , Ayanian Nora
Published: November 2022

Multirobot path planning and task assignment are traditionally treated separately, however task assignment can greatly impact the difficulty of the path planning problem, and the ultimate quality of solution is dependent upon both. We introduce task reassignment, an approach to optimally solving the coupled task assignment and path planning problems. We show that task reassignment improves solution quality, and reduces planning time in some situations.
Real-Time Optimization-Based Planning in Dynamic Environments Using GPUs
Authors: Park Chonhyon , Pan Jia , Manocha Dinesh
Published: November 2022

We present a novel algorithm to compute collision-free trajectories in dynamic environments. Our approach is general and makes no assumption about the obstacles or their motion. We use a replanning framework that interleaves optimization-based planning with execution. Furthermore, we describe a parallel formulation that exploits high number of cores on commodity graphics processors (GPUs) to compute a high-quality path in a given time interval. Overall, we show that search in configuration spaces can be significantly accelerated by using GPU parallelism.
Abstraction-Guided Sampling for Motion Planning
Authors: Kiesel Scott , Burns Ethan , Ruml Wheeler
Published: November 2022

Motion planning in continuous space is a fundamentalrobotics problem that has been approached from many per-spectives. Rapidly-exploring Random Trees (RRTs) usesampling to efficiently traverse the continuous and high-dimensional state space. Heuristic graph search methods uselower bounds on solution cost to focus effort on portions ofthe space that are likely to be traversed by low-cost solutions.In this work, we bring these two ideas together in a tech-nique called f -biasing: we use estimates of solution cost,computed as in heuristic search, to guide sparse sampling,as in RRTs. We see this new technique as strengthening theconnections between motion planning in robotics and combi-natorial search in artificial intelligence.
Polynomial-Time Construction of Contraction Hierarchies for Multi-Criteria Objectives
Authors: Funke Stefan , Storandt Sabine
Published: November 2022

In this paper we consider a variant of the multi-criteria shortest path problem where the different criteria are combined in an arbitrary conic combination at query time. We show that contraction hierarchies (CH) — a very powerful speed-up technique originally developed for standard shortest path queries (Geisberger et al. 2008) — can be adapted to this scenario and lead - after moderate preprocessing effort - to query times that are orders of magnitudes faster than standard shortest path approaches. On the theory side we prove via some polyhedral considerations that the crucial node contraction operation during the CH construction can be performed in polynomial-time, while on the more practical side we complement our theoretical results with experiments on real-world data. Our approach extends previous results (Geisberger, Kobitzsch, and Sanders 2010) which only considered the bicriteria case. This is an extended abstract of the full paper published in (Funke and Storandt 2013).
Target-Value Search Revisited (Extended Abstract)
Authors: Linares López Carlos , Stern Roni , Felner Ariel
Published: November 2022

This paper addresses the Target-Value Search (TVS) problem, which is the problem of finding a path between two nodes in a graph whose cost is as close as possible to a given target value T. This problem has been previously addressed only for directed acyclic graphs. In this work we develop the theory required to solve this problem optimally for any type of graphs. We modify traditional heuristic search algorithms for this setting, and propose a novel bidirectional search algorithm that is specifically suited for TVS. The benefits of this bidirectional search algorithm are discussed both theoretically and experimentally on several domains. A longer version of this work was accepted to IJCAI-2013 (Linares Lopez et al. 2013)
SoCS 2013 Organization
Authors: Helmert Malte , Röger Gabriele
Published: November 2022

List of organizers of the  Sixth International Symposium on Combinatorial Search.
Automatic Generation of Efficient Domain-Optimized Planners from Generic Parametrized Planners
Authors: Vallati Mauro , Fawcett Chris , Gerevini Alfonso , Hoos Holger , Saetti Alessandro
Published: November 2022

When designing state-of-the-art, domain-independent planning systems, many decisions have to be made with respect to the domain analysis or compilation performed during preprocessing, the heuristic functions used during search, and other features of the search algorithm. These design decisions can have a large impact on the performance of the resulting planner. By providing many alternatives for these choices and exposing them as parameters, planning systems can in principle be configured to work well on different domains. However, planners are typically used in default configurations that have been chosen because of their good average performance over a set of benchmark domains, with limited experimentation over the potentially huge range of possible configurations. In this work, we propose a general framework for automatically configuring a parameterized planner, and show that substantial performance gains can be achieved. We apply the framework to the well-known LPG planner, which in the context of this work was expanded to 62 parameters and over 6.5 x 10^17 possible configurations. By using this highly parameterized planning system in combination with the state-of-the-art automatic algorithm configuration procedure ParamILS, excellent performance on a broad range of well-known benchmark domains was achieved, as also witnessed by the results of the learning track of the 7th International Planning Competition.
Beyond Static Mini-Bucket: Towards Integrating with Iterative Cost-Shifting Based Dynamic Heuristics
Authors: Lam William , Kask Kalev , Dechter Rina , Ihler Alexander
Published: November 2022

We explore the use of iterative cost-shifting as a dynamic heuristic generator for solving MPE in graphical models via Branch and Bound. When mini-bucket elimination is limited by its memory budget, it may not provide good heuristics. This can happen often when the graphical model has a very high induced width with large variable domain sizes. In addition, we explore a hybrid setup where both MBE and the iterative cost-shifting bound are used in a combined heuristic. We compare these approaches with the most advanced statically generated heuristics.
Latent Features for Algorithm Selection
Authors: Malitsky Yuri , O'Sullivan Barry
Published: November 2022

The success and power of algorithm selection techniques has been empirically demonstrated on numerous occasions, most noticeably in the competition settings like those for SAT, CSP, MaxSAT, QBF, etc. Yet while there is now a plethora of competing approaches, all of them are dependent on the quality of a set of structural features they use to distinguish amongst the instances. Over the years, each domain has defined and refined its own set of features, yet at their core they are mostly a collection of everything that was considered useful in the past. As an alternative to this shotgun generation of features, this paper instead proposes a more systematic approach. Specifically, the paper shows how latent features gathered from matrix decomposition are enough for a linear model to achieve a level of performance comparable to a perfect Oracle portfolio. This information can, in turn, help guide researchers to the kinds of structural features they should be looking for, or even just identifying when such features are missing.
Bounded Suboptimal Search in Linear Space: New Results
Authors: Hatem Matthew , Ruml Wheeler
Published: November 2022

Bounded suboptimal search algorithms are usually faster than optimal ones, but they can still run out of memory on large problems. This paper makes three contributions. First, we show how solution length estimates, used by the current state-of-the-art linear-space bounded suboptimal search algorithm Iterative Deepening EES, can be used to improve unbounded-space suboptimal search. Second, we convert one of these improved algorithms into a linear-space variant called Iterative Deepening A* epsilon, resulting in a new state of the art in linear-space bounded suboptimal search. Third, we show how Recursive Best-First Search can be used to create additional linear-space variants that have more stable performance. Taken together, these results significantly expand our armamentarium of bounded suboptimal search algorithms.
UniAGENT: Reduced Time-Expansion Graphs and Goal Decomposition in Sub-optimal Cooperative Path Finding
Authors: Surynek Pavel
Published: November 2022

Solving cooperative path finding (CPF) by translating it to propositional satisfiability represents a viable option in highly constrained situations. The task in CPF is to relocate agents from their initial positions to given goals in a collision free manner. In this paper, we propose a reduced time expansion that is focused on makespan sub-optimal solving of the problem. The suggested reduced time expansion is especially beneficial in conjunction with a goal decomposition where agents are relocated one by one.
Red-Black Planning: A New Tractability Analysis and Heuristic Function
Authors: Gnad Daniel , Hoffmann Joerg
Published: November 2022

Red-black planning is a recent approach to partial delete relaxation, where red variables take the relaxed semantics (accumulating their values), while black variables take the regular semantics. Practical heuristic functions can be generated from tractable sub-classes of red-black planning. Prior work has identified such sub-classes based on the black causal graph, i.e., the projection of the causal graph onto the black variables. Here, we consider cross-dependencies between black and red variables instead. We show that, if no red variable relies on black preconditions, then red-black plan generation is tractable in the size of the black state space, i.e., the product of the black variables. We employ this insight to devise a new red-black plan heuristic in which variables are painted black starting from the causal graph leaves. We evaluate this heuristic on the planning competition benchmarks. Compared to a standard delete relaxation heuristic, while the increased runtime overhead often is detrimental, in some cases the search space reduction is strong enough to result in improved performance overall.
Focusing on What Really Matters: Irrelevance Pruning in Merge-and-Shrink
Authors: Torralba Álvaro , Kissmann Peter
Published: November 2022

Merge-and-shrink (M&S) is a framework to generate abstraction heuristics for cost-optimal planning. A recent approach computes simulation relations on a set of M&S abstractions in order to identify states that are better than others. This relation is then used for pruning states in the search when a "better" state is already known. We propose the usage of simulation relations inside the M&S framework in order to detect irrelevant transitions in abstract state spaces. This potentially simplifies the abstraction allowing M&S to derive more informed heuristics. We also tailor M&S to remove irrelevant operators from the planning task. Experimental results show the potential of our approach to construct well-informed heuristics and simplify the planning tasks prior to the search.
Position Paper: The Collapse Macro in Best-First Search Algorithms and an Iterative Variant of RBFS
Authors: Felner Ariel
Published: November 2022

This paper makes two pedagogical contributions. First, we describe two macrooperators for best-first search algorithms: the collapse macro where asubtree is deleted from memory and its best frontier value is stored in itsroot, and, the restore macro (the inverse of collapse) where thesubtree is restored to its previous structure. We show that many known searchalgorithms can be easily described by using these macros. The secondcontribution is an algorithm called Iterative Linear Best-first Search (ILBFS). ILBFS is equivalent to RBFS. While RBFS uses a recursive structure,ILBFS uses the regular structure of BFS with occasionally using the collapseand restore macros. ILBFS and RBFS are identical in the nodes that they visitand have identical properties. But, I believe that ILBFS is pedagogicallysimpler to describe and understand; it could at least serve as a pedagogicaltool for RBFS.
The Grid-Based Path Planning Competition: 2014 Entries and Results
Authors: Sturtevant Nathan , Traish Jason , Tulip James , Uras Tansel , Koenig Sven , Strasser Ben , Botea Adi , Harabor Daniel , Rabin Steve
Published: November 2022

The Grid-Based Path Planning Competition has just completed its third iteration. The entriesused in the competition have improved significantly during this time, changing the view ofthe state of the art of grid-based pathfinding. Furthermore, the entries from the competition have beenmade publicly available, improving the ability of researchers to compare their work. Thispaper summarizes the entries to the 2014 competition, presents the 2014 competition results,and talks about what has been learned and where there is room for improvement.
Learning to Search More Efficiently from Experience: A Multi-heuristic Approach
Authors: Aine Sandip , Sharma Charupriya , Likhachev Maxim
Published: November 2022

Learning from experience can significantly improve the performance of search based planners, especially for challenging problems like high-dimensional planning. Experience Graph (E-Graph) is a recently developed framework that encodes experiences, obtained from solving instances in the past, into a single bounded-admissible heuristic, and uses it to guide the search. While the E-Graph approach was shown to be very useful for repetitive problems, it suffers from two issues. First, computing the E-Graph heuristic is time consuming as it maintains the bounded admissibility constraints. Second, a single heuristic can get stuck in a local minimum, and thereby, degrade the performance. In this work, we present an alternative approach to improving the runtime of search from experience, based on a recently developed search algorithm Multi-heuristic A* (MHA*). This framework provides an improvement over the E-Graph planner for two reasons: a) MHA* uses multiple heuristics simultaneously to explore the search space, which reduces the probability of getting stuck in a local minimum, and b) the heuristics in MHA* can be arbitrarily inadmissible, which makes it very easy to compute them. The paper describes the framework, explains how to compute these (inadmissible) heuristics through offline and online processing and presents experimental analysis on two domains, motion planning for a 6D planar arm and large sliding tile puzzles.
Caching in Context-Minimal OR Spaces
Authors: Dechter Rina , Lelis Levi , Otten Lars
Published: November 2022

In empirical studies we observed that caching can have very little impact in reducing the search effort in Branch and Bound search over context-minimal OR spaces. For example, in one of the problem domains used in our experiments we reduce only by 1% the number of nodes expanded when using caching in context-minimal OR spaces. By contrast, we reduce by 74% the number of nodes expanded when using caching in context-minimal AND/OR spaces on the same instances. In this work we document this unexpected empirical finding and provide explanations for the phenomenon.
Recursive Constraint Manifold Subsearch for Multirobot Path Planning with Cooperative Tasks
Authors: Karkus Peter , Wagner Glenn , Choset Howie
Published: November 2022

The Cooperative Path Planning (CPP) problem seeks to determine a path for a group of robots which form temporary teams to perform tasks. The multi-scale effects of simultaneously coordinating many robots distributed across the workspace while also tightly coordinating the members of teams increases the difficulty of planning. Previous research produced the Constraint Manifold Subsearch (CMS) algorithm that can find minimal length paths to the CPP problem. However, CMS as currently formulated cannot handle more general cost functions, such as minimizing energy expenditure, and cannot handle task schedules that require multiple input teams to merge to form a set of multiple output teams. Furthermore, as CMS must couple planning for all interacting teams, it does not scale well to very large environments. In this paper, we rederive the CMS algorithm using a task graph to reason about inter-team dependencies, allowing the use of more general cost functions and task schedules. We then introduce the recursive CMS (rCMS) algorithm that exploits the reformulation to split the CPP into independent subproblems, significantly reducing computational complexity. Simulation studies show that rCMS can solve substantially larger problems than CMS.
A Multi-Phase Search Approach to the LEGO Construction Problem
Authors: Stephenson Ben
Published: November 2022

The task of determining which LEGO bricks to use to construct a volume is known as the LEGO Construction Problem. This is a challenging problem because even small volumes can be constructed in a tremendously large number of ways. As a result, an exhaustive search is impractical, and more nuanced search strategies must be employed to find a good, though not necessarily optimal, solution. This paper describes a multi-phase search approach to the LEGO Construction Problem. Our first search phase uses heuristics to identify a moderate number of candidates for each layer in the model. This is followed by two different search strategies which identify alternative brick arrangements that reduce the number of connected components, undesirable edges, and bricks in the model. A final highly localized search is applied to bricks at the boundaries between the model's connected components if the previous search processes fail to reduce the model to a single connected component. Applying this four-phase search strategy to a diverse selection of models has demonstrated that it normally finds a result that consists of a single connected component when such a solution exists, and that the models are structurally sound when built.
Burnt Pancake Problem: New Lower Bounds on the Diameter and New Experimental Optimality Ratios
Authors: Bouzy Bruno
Published: November 2022

For the burnt pancake problem, we provide new values of g(-IN), new hard positions and new experimental optimality ratios.
Numeric Planning via Search Space Abstraction (Extended Abstract)
Authors: Illanes León , McIlraith Sheila
Published: November 2022

Many real-world planning problems are best modeled as infinite search space problems, using numeric fluents. Unfortunately, most planners and planning heuristics do not directly support such fluents. We propose a search space abstraction technique that compiles a planning problem with numeric fluents into a finite state propositional planning problem. To account for the loss of precision resulting from the abstraction, we leverage a policy repair technique used for non-deterministic planning. We evaluate our approach on a set of benchmarks and compare it to state-of-the-art planners that deal with numeric fluents.
Solving Graph Optimization Problems in a Framework for Monte-Carlo Search
Authors: Edelkamp Stefan , Externest Eike , Kühl Sebastian , Kuske Sabine
Published: November 2022

In this paper we solve fundamental graph optimization problems like Maximum Clique and Minimum Coloring with recent advances of Monte-Carlo Search. The optimization problems are implemented as single-agent games in a generic state-space search framework, roughly comparable to what is encoded in PDDL for an action planner.
On Variable Dependencies and Compressed Pattern Databases
Authors: Helmert Malte , Sturtevant Nathan , Felner Ariel
Published: November 2022

Pattern databases are among the strongest known heuristics for many classical search benchmarks such as sliding-tile puzzles, the 4-peg Towers of Hanoi puzzles, Rubik's Cube, and TopSpin. Min-compression is a generally applicable technique for augmenting pattern database heuristics that has led to marked experimental improvements in some settings, while being ineffective in others. We provide a theoretical explanation for these experimental phenomena by studying the interaction between the ranking function used to order abstract states in a pattern database, the compression scheme used to abstract states, and the dependencies between state variables in the problem representation.
Fast and Almost Optimal Any-Angle Pathfinding Using the 2k Neighborhoods
Authors: Hormazábal Nicolás , Díaz Antonio , Hernández Carlos , Baier Jorge
Published: November 2022

Any-angle path finding on grids is an important problem with applications in autonomous robot navigation. In this paper, we show that a well-known pre-processing technique, namely subgoal graphs, originally proposed for (non any-angle) 8-connected grids, can be straightforwardly adapted to the 2k neighborhoods, a family of neighborhoods that allow an increasing number of movements (and angles) as k is increased. This observation yields a pathfinder that computes 2k-optimal paths very quickly. Compared to ANYA, an optimal true any-angle planner, over a variety of benchmarks, our planner is one order of magnitude faster while being less than 0.0005% suboptimal. Important to our planner's performance was the development of an iterative 2k heuristic, linear in k, which is also a contribution of this paper.
Extended Abstract: The Heuristic Search Research Framework
Authors: Goldenberg Meir
Published: November 2022

This paper is an extended abstract of the recently published journal article (M. Goldenberg, The Heuristic Search Research Framework. Knowledge-Based Systems 129: 1–3. 2017). The Heuristic Search Research Framework is a software framework for implementing heuristic search algorithms and exploring their properties. The framework uses policy-based design to enable efficient, flexible and well-organized implementations. In addition, the framework provides effective tools for exploring the properties of the implemented algorithms. The extensive online documentation includes a video demo.
Robust Multi-Agent Path Finding
Authors: Atzmon Dor , Stern Roni , Felner Ariel , Wagner Glenn , Bartak Roman , Zhou Neng-Fa
Published: November 2022

In the multi-agent path-finding (MAPF) problem, the task is to find a plan for moving a set of agents from their initial locations to their goals without collisions. Following this plan, however, may not be possible due to unexpected events that delay some of the agents. We explore the notion of k-robust MAPF, where the task is to find a plan that can be followed even if a limited number of such delays occur. k-robust MAPF is especially suitable for agents with a control mechanism that guarantees that each agent is within a limited number of steps away from its pre-defined plan. We propose sufficient and required conditions for finding a k-robust plan, and show how to convert several MAPF solvers to find such plans. Then, we show the benefit of using a k-robust plan during execution, and for finding plans that are likely to succeed.
A Suboptimality Bound for 2k Grid Path Planning
Authors: Kramm Benjamín , Rivera Nicolas , Hernandez Carlos , Baier Jorge
Published: November 2022

The 2k neighborhood has been recently proposed as an alternative to optimal any-angle path planning over grids. Even though it has been observed empirically that the quality of solutions approaches the cost of an optimal any-angle path as k is increased, no theoretical bounds were known. In this paper we study the ratio between the solutions obtained by an any-angle path and the optimal path in the 2kk, that generalizes previously known bounds for the 4- and 8-connected grids. We analyze two cases: when vertices of the search graph are placed (1) at the corners of grid cells, and (2) when they are located at their centers. For case (1) we obtain a suboptimality bound of 1 + 1/8k2 + O(1/k3), which is tight; for (2), however, worst-case suboptimality is a fixed value, for every k ≤ 3. Our results strongly suggests that vertices need to be placed in corners in order to obtain near-optimal solutions. In an empirical analysis, we compare theoretical and experimental suboptimality.
On the Complexity of Quantum Circuit Compilation
Authors: Botea Adi , Kishimoto Akihiro , Marinescu Radu
Published: November 2022

Quantum circuit compilation (QCC) is an important problem in the emerging field of quantum computing. The problem has a strong relevance to combinatorial search, as solving approaches recently published include constraint programming and temporal planning. In this paper, we focus on a complexity analysis of quantum circuit compilation. We formulate a makespan optimization problem based on QCC, and prove that the problem is NP-complete. To the best of our knowledge, this is the first study on the theoretical complexity of QCC.
Rapid Randomized Restarts for Multi-Agent Path Finding Solvers
Authors: Cohen Liron , Wagner Glenn , Chan David , Choset Howie , Sturtevant Nathan , Koenig Sven , Kumar T. K.
Published: November 2022

Multi-Agent Path Finding (MAPF) is an NP-hard problem that has been well studied in artificial intelligence and robotics. Recently, randomized MAPF solvers have been shown to exhibit heavy-tailed distributions of runtimes, which can be exploited to boost their success rate for a given runtime limit. In this paper, we discuss different ways of randomizing MAPF solvers and evaluate simple rapid randomized restart strategies for state-of-the-art MAPF solvers such as iECBS, M* with highways and CBS-CL.
Domus Capitalismi: Abstract Spaces and Domesticated Subjectivities in Times of Covid-19
Authors: Briziarelli Marco , Armano Emiliana
Published: November 2022

This chapter investigates the relation of digital labour and urban space production in the time of the Covid-19 pandemic and in the broader context of a capitalism crisis. From a theoretical and interpretative approach, our inquiry posits the Covid-19 social production of space as a lens to assess the dialectics of capitalist crises, which imply both how digital spatial remedies are powered by machinic fix capital and the contradictory positionality of domesticated subjectivities. We argue that the Covid-19 pandemic-induced circulatory crisis has prompted a compensatory response that has been described as digital spatial fix, which combines measures against the crisis as well as subsumptive phenomena mainly under capitalist forms such as digital abstract space and machinic fix capital. We will exemplify this by examining how the private residences of many workers are being subsumed as digital abstract space (i.e., a logistical space constituted by the synergic encounter between digital platforms and subjects that operate in machinic fashion) are shaped by multiple overlapping spheres of action, which makes them domesticated.
Black Box Power: Zones of Uncertainty in Algorithmic Management
Authors: Heiland Heiner
Published: November 2022

This chapter examines algorithmic management and investigates its mechanisms. It is argued that the existing discussion is partly characterised by technological determinism, which firstly assumes comprehensive control and secondly narrows the view to technological aspects. Drawing on the organisation theory of Michel Crozier and Erhard Friedberg, the limited agency of heteronomous actors is analysed. The focus is on the opacity of algorithmic structures, which contributes decisively to the effectiveness of algorithmic management. This mechanism is identified as black box power, leading to an algorithmic self which monitors its actions carefully and is obedient in an anticipatory manner.
The Digital Traces of Crypto-Finance
Authors: Cossu Alberto
Published: November 2022

The data made available by the digitisation of social life has revolutionised the behaviour of financial amateurs investing in crypto currencies, created in the aftermath of the Blockchain revolution. Knowledge of the actions of others was always a preoccupation for investors in every market as it played a pivotal role in the creation of financial profit: the less that key information was known to the public, the more it was valuable. Now, the regime of visibility is reverted: what was once secret is now publicly disseminated on the web. Amateur investors discuss potentially lucrative currencies online, where they are also socialised to the new practices and ethos of digital finance via YouTube videos and, most importantly, they coordinate their actions in online chat apps, such as Telegram or Discord. This chapter explores the new role of information production and creation in the functioning of crypto-financial markets. The digital traces left by amateur investors across the web call for an updated understanding of the cultural ideology operating beneath this financial revolution where an apparently perfect symmetry of information is coupled with universally accessible digital ledgers. Based on digital data gathering and content analysis this chapter argues that such digital traces empower new investors with unprecedented possibilities for creating value and, at the same time, are subject to massive data gathering activities by companies that analyse and sell aggregated behavioural information.
Performed Subjectivities in Ranking and Recommendation Systems
Authors: Mazali Tatiana , Gay Nicoletta
Published: November 2022

Creative professions were among the first to be affected by the algorithmic logic of online reputational mechanisms, rating processes, evaluations and measurements, and creative workers were among the first to highlight the critical aspects of the so-called algorithmic self and its impact on labour practices. In some regards, supply and demand platforms dedicated to creative services have paved the way for ‘factory-model’ subjectivities evaluated by algorithms. Certain creative work dynamics have been exacerbated by the need to digitally position oneself through personal branding and self-marketing. This chapter focuses on the socio-technical dimensions which heavily impact on all those professions for which one’s online positioning is important, a position which is affected by reputation and recommendation models on social networks, and algorithms inside ranking systems. More specifically, the chapter analyses the functioning of rankings on Facebook, discussing this point within the debate on how and whether to humanise algorithms, making them less ‘unfair’.
The Social Costs of the Gig Economy and Institutional Responses: Forms of Institutional Bricolage in Italy, France and the Netherlands
Authors: Franzini Maurizio , Lucciarini Silvia
Published: November 2022

This chapter, based on a field research conducted in three countries, focuses on gig workers (in particular on and off-platform), who are facing specific social costs such as precarization and instability, induced by emerging new technologies. Our main concern is whether institutions have changed in a way that would enable them to reduce the burden of these costs and, if so, to explore these changes. Historically, trade unions have been the main actor working to defend and extend workers’ rights and to protect and improve working conditions. Several other quasi-collective actors have emerged as self-employment spread, which were not always coordinated with unions, particularly in the field of social and mutual aid cooperatives and of professional associations. These emerging actors have made the overall landscape of representation much more complex. Scholars have studied these new organizations of representation and aggregation for self-employed workers predominantly by framing them as external to the traditional system of industrial relations or as bottom-up initiatives with a limited power of action. Our main argument is that the relations between old and new institutional actors are crucial, and the possibility of developing adaptation or innovative strategies also depends on them. With this perspective, it is necessary to pay the utmost attention to the state, which can play a no less important role with new organizations for the self-employed than it has had in fostering collective bargaining in the classical system of industrial relations. Moreover, evidence from fieldwork suggests that these relationships have the character of ‘institutional bricolage’, as old and new institutional actors attempt to perform new functions to adapt configurations of rules and practices to new conditions.
Como hacer el derecho con palabras
Authors: Patiño-Arango Alejandro
Published: November 2022

Desde nuestro nacimiento nos encontramos con una multiplicidad de situaciones que van desde nuestro estado natural, al estado social y de este al estado político. Aunque cada una de estas situaciones parece normal, cada una de ellas está regida por contextos diferentes. Estas corresponden a tres estados: de naturaleza, social y jurídicopolítico.
En este artículo mostraré como se hace el derecho con palabras. Idea que se expone a través de la teoría de los performativos de Austin y la cual Olivecrona aplica al lenguaje jurídico. Esto significa que para elaborar cualquier tipo de pacto institucional, previo a este, es esencial el pacto lingüístico como lo concibe Hobbes en el Leviatán. Sin embargo, en la construcción del pacto institucional, también es necesario un lenguaje regido por reglas tal como lo concibe Searle al analizar las reglas institucionales. Reglas que son fundamentales para el lenguaje jurídico.
Democracia y crisis : una breve valoración de la democracia constitucional en tiempos de pandemia.
Authors: Jiménez Ramírez Milton César
Published: November 2022

La democracia es un procedimiento ético civil para resolver problemas, diferencias y adoptar decisiones a través de la regla de mayorías. Este es un concepto básico de democracia. La democracia es regulada y protegida a través de las constituciones que la estipulan como un principio estructural al lado de la separación de poderes, el principio de legalidad, los derechos humanos y sus garantías. Además, la democracia es el método más legítimo para el desarrollo de las constituciones. De hecho, es el desarrollo y la práctica de la democracia la que asegura que la constitución sea un proceso viviente (Ackerman, 2011), una evolución constante, y que pueda adaptarse mejor a los desafíos de los hechos que pretenden desplazarla, sustituirla o mutarla, e incluso desconocer la moralidad política que la constitución le impone a la democracia (Nino, 1997). Esto es, la democracia no puede ser una radical que toma decisiones por encima de los derechos de las minorías, sin deliberación social e institucional, solo amparada en el hecho de ser una decisión mayoritaria.
Anotaciones sobre la noción de pobreza desde el desarrollo sostenible
Authors: Orjuela Artunduaga Hanna Marietta , Ramírez Ospina Duván Emilio
Published: November 2022

Partiendo de la idea que erradicar la pobreza es un anhelo transversal en los Objetivos de Desarrollo Sostenible, el propósito de este estudio consiste en contribuir a la instrumentalización del desarrollo sostenible, identificando las tendencias de la manera como la comunidad científica ha pensado la articulación entre los conceptos de pobreza y desarrollo sostenible, interpretación que a su vez permite estandarizar los criterios para explicar la pobreza en el marco del desarrollo sostenible y hacer inferencias sobre posibles líneas de investigación en torno a esa articulación, todos los resultados se obtienen con una cienciometría o revisión sistemática de literatura científica que sigue fases sucesivas de planeación, búsquedaselección, análisis y prospectiva. A partir de la revisión sistemática de literatura, se evidencia que la pobreza en articulación con el desarrollo sostenible se constituye en un tema de alto interés para la  comunidad científica, que se viene desarrollando mediante cinco tendencias o líneas de investigación: actividades productivas sostenibles, propuestas de indicadores de pobreza, diseño de metodologías y modelos, interpretación y análisis de los avances de los Objetivos de Desarrollo Sostenible y otros temas relacionado con elementos de las tres dimensiones del desarrollo sostenible. Los resultados aquí observados se pueden emplear en futuras investigaciones como un punto de partida para concebir y repensar la pobreza desde la noción del desarrollo sostenible.
Transosteal radial free flap in palate reconstruction
Authors: Luis Nieto , Oscar De León , Rolf Smit , Zamir Paéz , Camilo Cháves
Published: November 2022

The reconstruction of the palate has been a challenge for the reconstructive surgeon, due to the multiple complications that arise, such as infection, dehiscence, and fall of the flap used. We present the description of a new radial free flap fixation technique, commonly used for this type of reconstruction. This transosteal fixation technique prevents dehiscence and flap descent in all cases performed, by combining two widely used procedures, the radial free flap, and the Lefort I osteotomy, with excellent results.
Mortality and survival of patients with rheumatoid arthritis and symptomatic diffuse interstitial lung disease
Authors: M Gema Bonilla-Hernán , Luis Gómez-Carrera , María Fernández-Velilla Peña , Chamaida Plasencia-Rodríguez , Pilar Aguado , Rodolfo Álvarez-Sala Walther , Alejandro Balsa
Published: November 2022

Introduction: In Spain, few data have been reported on mortality and survival in rheumatoid arthritis with diffuse interstitial lung disease. Objectives: To estimate mortality and survival for patients with symptomatic diffuse interstitial lung disease and rheumatoid arthritis and to analyze the effect of clinical factors. Methods: We performed an observational study between 2007 and 2018 at the Interdisciplinary Rheumatology and Pulmonology Clinic, from a tertiary Hospital. Patients with rheumatoid arthritis and symptomatic of diffuse interstitial lung disease confirmed by high-resolution computed tomography were included. Causes of death and clinical factors were reported. Results: We identified 90 patients with rheumatoid arthritis and symptomatic interstitial lung disease. Twenty-six patients died and diffuse interstitial lung disease was the most frequent cause (50%). The overall mortality rate was 19.7 per 1000 patient-years (95% CI: 13.4 - 29). The multivariate model revealed the predictors of mortality to be a long time between diagnosis of rheumatoid arthritis and lung involvement (HR = 1.17; p = 0.003) and low forced vital capacity (HR = 0.02; p = 0.018). The probability of survival was 50% at 10.2 years from diagnosis of interstitial lung disease. Comparison of survival did not reveal significant differences by type of radiologic pattern (p = 0.823). Conclusions: The fact that almost one-third of patients died and that survival is 50% at 10 years highlights the important role of diffuse interstitial lung disease in rheumatoid arthritis. The radiologic pattern does not seem to be as important for survival as forced vital capacity at diagnosis and the time between diagnosis of rheumatoid arthritis and lung involvement. Key points 1. DILD is associated with shorter survival in patients with RA. 2. The radiologic pattern does not seem to influence the survival in patients with RA and DILD. 3. The FVC at diagnosis is an important factor that influences the prognosis of patients with RA and DILD.
Amplification and sequencing of Hepatitis B virus pol gene v1
Authors: not provided rute.marcelino
Published: November 2022

TheAmplification and sequencing of HBV pol gene protocol aim to present all the details from HBV DNA extraction with QIAamp DNA Blood Mini Kit (Qiagen, Werfen) and with a homemade assay for amplification/sequencing of the RT region of the HBV pol gene. This protocol is related to an ongoing publication from PLOS ONE.
Language Learning With Neurolinguistic Programming: An Integrative Review
Authors: Rustan Edhy
Published: November 2022

The neurolinguistic programming (NLP) approach is being widely applied in learning. However, there are no review articles related to the application of NLP in language learning. This review aims to present a synthesis of literature on the effectiveness of NLP application in language learning in terms of methods, learning aspects, changes in language skills, and student learning psychology. An integrative review was conducted using five databases, namely, EBSCO, Wiley, ProQuest, ScienceDirect, and JSTOR. Keywords were used to search for and collect data in English related to language learning using the NLP approach published from 2011 to 2021. Based on the 15 articles reviewed, the visual, auditory, and kinesthetic (VAK) learning method is most often applied in language learning. Most teachers use NLP in language learning in speaking and writing skills. Applying the NLP method in language learning can improve students’ language skills and change students’ psychological learning in a positive direction
Marriage Break-Ups and Its Effect on Children’s Future: An Exploration of the Novel Custody
Authors: V Jayajothilakshmi , S Mohan , R Kannan
Published: November 2022

Marriage life needs true commitment, love and respect. Many marriage couples today lack understanding which results in break-ups and divorces. This affects the couple as well as their children. Successful marriage with the couple’s loyalty and love make their children grow up in a pleasant atmosphere with good mindset. Optimistic approach of parents, their sacrifice and care among the family members give progressive societal environment to children. The present generation of children is very intellectual in scrutinizing the happenings around them and hence parents need to keep the surrounding perfect. Parental care and secure life are the principal things to be given to the children for their future life. When trust and respect between a husband and wife are ruined, children’s trust and respect on their parents will too be spoiled. Especially the separation between a husband and a wife affects their children’s future. Their lack of concentration on their children leads their lives to a drastic hole which results in devastation of their future. This study focuses on marriage break-ups and how parents’ lifestyle affects children and their holistic growth. It has been applied in Manju Kapur’s novel Custody which portrays marriage bond through a middle-class family and explains the impact of husband and wife’s controversies on children. The existing condition of many families and general issues have been analyzed deeply and presented with reference to the novel. This research article represents essential needs of strong marriage bond and the significance of parents’ love for the betterment of children’s life.
E-Learning and Social Media for ELT — Teachers’ Perspective
Authors: Paliath Gayathri , Evangeline Marie
Published: November 2022

English as a foreign language poses many difficulties to teach and to learn; the problem gets further intense when English has to be used as a medium of instruction to teach other subjects. There is a definite need to support foreign language learners by extending the learning and instruction outside the classroom. There is a growing realization of the role of social media in learning / teaching, especially of English language. Handheld devices like mobiles and tablets, laptops and desktops are all possible means to access social media apps. Such social media apps, along with search engines and conferencing apps form an essential toolkit for learning and instruction outside the physical classrooms. Mobiles and internet have become popular for e-learning due to their features such as ubiquity, interactivity and portability. A lot of research has been done globally on the students’ perspective for the use of extended English language learning outside the classroom through social media apps and audio/video conferencing. A study on the experiences and observations of the teachers on teaching through such means revealed that teachers perceive social media and e-learning very useful and effective for English learning and instruction. Teachers find such means definitely useful for the preparation and conduct of the classes. While social media and e-learning for teaching English is not without some drawbacks, the positives of such means for ELT far outweigh the negatives. This paper describes the use of social media in English classroom and proposes a practical way to make the best use of it.
Postural balance, muscle strength and functional capacity on the severity level of chronic obstructive pulmonary disease
Authors: Sera Kim Fabiana , Aguilar Zarpellão Karlla , Marília Tadayeski Peyres  , Marcos Eduardo SCheicher  , Ambrozin Alexandre Ricardo Pepe
Published: November 2022

Background: Chronic obstructive pulmonary disease (COPD) is characterized by persistent and progressive airflow obstruction. It is a lung disease with systemic manifestations, which contributes to an increase in morbidity and mortality in the elderly. The greater the severity of the disease, more muscle loss occurs, especially the quadriceps muscle, leading to decreased resistance to exercise, increased fatigue, and dyspnea to small efforts. The presence of COPD is associated with an increased risk of falls, and patients with COPD have a greater imbalance when compared with subjects of the same age without the disease.  To investigate whether the different degrees of severity of COPD interfere in the balance, muscle strength, and functional capacity of the patients. Methods: 25 individuals diagnosed with COPD (COPD-G) and 32 individuals without pulmonary disease (CG - Control Group) were assessed. Both groups were submitted to anamnesis, spirometry, dynamometry, manovacuometry, Incremental Shuttle WaIking Test (ISWT), load testing for one repetition maximum (1RM), balance platform assessment, Stair-Climbing Test (SCT) and 6 Minutes Walk Test (6MWT). The variables obtained were compared using the t-test. For comparison between groups, a one-way ANOVA was used. Results: The comparison between the two groups showed a difference in the result of the ISWT, 6MWT and SCT. When compared between groups in different degrees of severity, there was a difference only in SCT between CG and severe COPD-G. There was no significant difference in strength and postural balance. Conclusion: Cardiorespiratory functional capacity is impaired in individuals with COPD and is more evident in the severe stage of the disease. The balance, the strength of the respiratory muscles, upper and lower limbs are similar in the mild, moderate, and severe stages.