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This paper presents a systematic methodology for analyzing and optimizing an innovative antenna mount designed for phased array antennas, implemented through a novel 2-PSS&1-RR circular-rail parallel mechanism. Initially, a comparative motion analysis between the 3D model of the mount and its full-scale prototype is conducted to validate effectiveness. Given the inherent complexity, a kinematic mapping model is established between the mount and the crank-slider linkage, providing a guiding framework for subsequent analysis and optimization. Guided by this model, feasible inverse and forward solutions are derived, enabling precise identification of stiffness singularities. The concept of singularity distance is thus introduced to reflect the structural stiffness of the mount. Subsequently, also guided by the mapping model, a heuristic algorithm incorporating two backtracking procedures is developed to reduce the mount's mass. Additionally, a parametric finite-element model is employed to explore the relation between singularity distance and structural stiffness. The results indicate a significant reduction (about 16%) in the antenna mount's mass through the developed algorithm, while highlighting the singularity distance as an effective stiffness indicator for this type of antenna mount. [ABSTRACT FROM AUTHOR]

The transition to a low-carbon economy is one of the main challenges of our time. In this context, solar energy, along with many other technologies, has been developed to optimize performance. For example, solar trackers follow the sun's path to increase the generation capacity of photovoltaic plants. However, several factors need consideration to further optimize this process. Important variables include the distance between panels, surface reflectivity, bifacial panels, and climate variations throughout the day. Thus, this paper proposes an artificial intelligence-based algorithm for solar trackers that takes all these factors into account—mainly weather variations and the distance between solar panels. The methodology can be replicated anywhere in the world, and its effectiveness has been validated in a real solar plant with bifacial panels located in northeastern Brazil. The algorithm achieved gains of up to 7.83% on a cloudy day and obtained an average energy gain of approximately 1.2% when compared to a commercial solar tracker algorithm. [ABSTRACT FROM AUTHOR]

Background: To minimize measurement uncertainties and create seamless procedures between tests and simulations for the characterization and prediction of damage in large scale structures, a system capable of monitoring the quantities of interest at different scales throughout the test is required. Objective: The aim of this work is to develop a multiview DIC framework at varying scales in which kinematic fields are expressed on a unique mesh. Methods: A three-point flexural test was performed on a concrete beam and the images acquired by three different cameras were used to perform DIC calculations. Results: Displacement and strain fields were measured using mono and multiview implementations; their associated uncertainties were assessed. Damage initiation and growth within the sample was quantified based on the standard displacement uncertainty. Conclusion: The reported results show that the proposed method reduced the associated displacement uncertainties. The onset and propagation of damage was successfully quantified. [ABSTRACT FROM AUTHOR]

Ocean currents, driven by gravity, wind, and water density, disperse marine biota worldwide, often leading species to shorelines alive or as carcasses. These carcasses provide vital information about species' health conditions and threats within their habitats. Marine animal strandings thus offer crucial insights into the ecological implications of population mortality. This research is instrumental for conservation efforts and identifying trends and threats. Scientists use human and animal forensics approaches to trace the origins of beached bodies. The capability to backtrack carcass drift and estimate death sites helps evaluate anthropogenic impacts. This information also forms the basis for legal applications and gives ecological indicators for marine megafauna conservation. Using backtracking in forensic ecology for conservation research presents expansive investigative opportunities. This paper offers a comprehensive review of: 1) Physical and environmental processes; 2) Drift applications; 3) Marine megafauna examples; 4) Forensic principles; 5) Postmortem intervals; 6) Marine megafauna backtracking. We further discuss these findings' potential conservation applications for endangered species. Our review aims to enhance understanding of coastal animal distribution, estimate mortality rates from strandings, explore seasonal variations for beach monitoring programs, and investigate anthropogenic impacts.

System provenance forensic analysis has been studied by a large body of research work. This area needs fine granularity data such as system calls along with event fields to track the dependencies of events. While prior work on security datasets has been proposed, we found a useful dataset of realistic attacks and details that are needed for high-quality provenance tracking is lacking. We created a new dataset of eleven vulnerable cases for system forensic analysis. It includes the full details of system calls including syscall parameters. Realistic attack scenarios with real software vulnerabilities and exploits are used. For each case, we created two sets of benign and adversary scenarios which are manually labeled for supervised machine-learning analysis. In addition, we present an algorithm to improve the data quality in the system provenance forensic analysis. We demonstrate the details of the dataset events and dependency analysis of our dataset cases. [ABSTRACT FROM AUTHOR]

With the rapid development of multimedia technology, it is very important to improve the accuracy of sparse signal reconstruction for image or speech based on compressed sensing technology. In this work, a matching pursuit algorithm for sparse signal reconstruction based on Jaccard coefficient and backtracking strategy is proposed to improve the accurate reconstruction probability. Jaccard coefficient matching criterion and inner product matching criterion are combined to preserve more features of the original vector. A mean-based thresholding strategy is used to selects atoms adaptively, and the backtracking method is introduced to filter out the wrong atoms. Experimental results show that the reconstruction performance of the proposed algorithm is much better than other greedy algorithms when the sparsity K is large (K>35). For speech signals, the proposed algorithm has better reconstruction performance than other algorithms for both male and female voice signals. Under different compression ratios, the AFSNR and the PESQ scores of the reconstructed speech by the proposed algorithm are increased by at least 1.5348 dB and 0.5629, respectively, especially showing superior performance under larger compression ratio. The proposed algorithm has bright application prospect in intelligent speech interaction with accurate reconstruction of speech signal under large compression ratios. [ABSTRACT FROM AUTHOR]

The transition to a low-carbon economy is one of the main challenges of our time. In this context, solar energy, along with many other technologies, has been developed to optimize performance. For example, solar trackers follow the sun’s path to increase the generation capacity of photovoltaic plants. However, several factors need consideration to further optimize this process. Important variables include the distance between panels, surface reflectivity, bifacial panels, and climate variations throughout the day. Thus, this paper proposes an artificial intelligence-based algorithm for solar trackers that takes all these factors into account—mainly weather variations and the distance between solar panels. The methodology can be replicated anywhere in the world, and its effectiveness has been validated in a real solar plant with bifacial panels located in northeastern Brazil. The algorithm achieved gains of up to 7.83% on a cloudy day and obtained an average energy gain of approximately 1.2% when compared to a commercial solar tracker algorithm.

The autonomous navigation technology of INS has always attracted the attention of many scholars. In satellite-denied environment, making full use of the auxiliary sensors with autonomous characteristics can suppress the dynamic error generated by INS in autonomous navigation effectively. However, auxiliary sensors like an odometer (OD) and laser doppler velocimeter (LDV) will cause instability to the navigation system. To solve the above problems, we propose an improved autonomous inerital-based integrated navigation scheme utilizing vehicle motion recognition. The main research work can be summarized as: (1) Non-holonomic constrained velocity model and tri-axis zero velocity model has been established for inertial-based integrated navigation model. (2) Vehicle motion state recognition method has been proposed utilizing the IMU data. As shown in the experimental results, the proposed method can estimate the IMU biases and increase the positioning accuracy effectively as compared with the traditional methods.

Sudoku is a complicated multidimensional mathematical structure with several applications in various computer science domains. 3D Sudoku, compared to 2D, has one more dimension that can potentially provide an extra edge in the field of different application areas. Several researchers have developed various types of 2D Sudoku solvers using different methodologies. However, there is very limited research in the area of developing 3D Sudoku solvers. Thus, two different solvers for solving 3D Sudoku puzzles of size $9\times 9 \times 9$ are proposed in this work. Both solvers provide all possible solutions for solving a 3D Sudoku puzzle. 2D Sudoku puzzles are applied in different research domains with different purposes. Recently, 3D structure of Sudoku has been applied in several areas to achieve more effectiveness compared to 2D Sudoku. Additionally, it can also be used to solve problems in 3D space. Again, solving an NP-complete puzzle by considering its 3D structure is a challenging job. Thus, we endeavoured to achieve all probable solutions for a 3D Sudoku instance in this work. In the first version of our proposed algorithm, all possible values for each blank cell are computed and stored. Subsequently, a few elimination-based methods are used to reduce the number of probable values (if possible) for each blank cell. Finally, the solutions are computed using the backtracking method. In the second version of our proposed algorithm, the nine 2D Sudoku puzzles, lying in the $xz$ -plane one above the other, which form the 3D puzzle are fed as the input. All possible solutions are obtained for each of the nine puzzles. Then, the obtained solutions are mapped to achieve one or more solutions for the 3D Sudoku instance. Thus, our proposed techniques provide a new approach for solving 3D Sudoku. In addition, applying the obtained solutions provides us with an advantage over 2D Sudoku, in solving problems in the 3D space and where more data is required.

Transcription elongation by multi-subunit RNA polymerases (RNAPs) is regulated by auxiliary factors in all organisms. NusG/Spt5 is the only universally conserved transcription elongation factor shared by all domains of life. NusG is a component of antitermination complexes controlling ribosomal RNA operons, an essential antipausing factor, and a transcription-translation coupling factor in Escherichia coli. We employed RNET-seq for genome-wide mapping of RNAP pause sites in wild-type and NusG-depleted cells. We demonstrate that NusG is a major antipausing factor that suppresses thousands of backtracked and nonbacktracked pauses across the E. coli genome. The NusG-suppressed pauses were enriched immediately downstream from the translation start codon but were also abundant elsewhere in open reading frames, small RNA genes, and antisense transcription units. This finding revealed a strong similarity of NusG to Spt5, which stimulates the elongation rate of many eukaryotic genes. We propose a model in which promoting forward translocation and/or stabilization of RNAP in the posttranslocation register by NusG results in suppression of pausing in E. coli. [ABSTRACT FROM AUTHOR]

The simplified partial digest problem (SPDP) models an effective and robust method for the building of a physical map using restriction site analysis. The best known algorithm requires O(n2n) time, using O(n2n) working space. The high complexities in time and space impede its application to genomes of a large number of sites. This article gives two new algorithms. The first improves the time by a factor of O(n) and significantly reduces the space to O(n2). The second improves both the time and space to O(n1.52n/2). Extensive experiments are conducted on real genomes. For instances that can be solved by the best known algorithm, the new algorithms achieve a speedup of up to 4000 times; in addition, due to the reduction in space, the new algorithms can solve many more instances. Experiments also reveal the following advantage of the SPDP method: almost every instance has at most four feasible solutions and for an instance that does not contain any pair of symmetric restriction sites, in all observed examples, the solution is unique. [ABSTRACT FROM AUTHOR]

This study demonstrates the use of environmental tracers (Water isotopes-δ18O–δ2H, Radon-222Rn, and Electrical Conductivity-EC) as complementary tools for backtracking the water source, estimating pipe water residence time, and monitoring the instability of the water quality. Using the capital of Ethiopia, Addis Ababa, as a case study site, we demonstrate that water isotopes (δ18O andδ2H) effectively backtrack the tap water to its source (springs, reservoirs, shallow aquifers, or deep aquifers). 222Rn is shown to be effective for discriminating groundwater-sourced pipe networks from those that are dominated by surface waters. Our reconnaissance survey reveals that 222Rn, a tracer previously not considered to determine the pipe water residence time, can be used effectively to determine pipe water residence time in groundwater-sourced pipe networks. We recommend further research to explore the capability of 222Rn as a robust indicator of the pipe water residence time in an urban piped water network. The tracers reveal that 50% of the city obtains its water from groundwater and that the groundwater-sourced areas of the city show the highest water quality instability. The water quality in groundwater-sourced pipes varies depending on pumping stoppage owing to power interruptions. Surface water-sourced pipe water shows seasonal variations in water quality, with occasional large deviations from the normal trends following flow interruptions.

Modernization and the ever-increasing trend of introducing modern technologies into various areas of everyday life require school graduates with programming skills. The ability to program is closely related to computational thinking, which is based on algorithmic thinking. It is well known that algorithmic thinking is the ability of students to work with algorithms understood as a systematic description of problem-solving strategies. Algorithms can be considered as a fundamental phenomenon that forms a point of contact between mathematics and informatics. As part of an algorithmic graph theory seminar, we conducted an experiment where we solved the knight's tour problem using the backtracking method to observe the change in students' motivation to learn algorithms at a higher cognitive level. Seventy-four students participated in the experiment. Statistical analysis of the results of the experiment confirmed that the use of the algorithm with decision-making in teaching motivated students to learn algorithms with understanding. [ABSTRACT FROM AUTHOR]

El sistema de seguimiento horizontal de un eje (HSAT) ajusta la orientación Este-Oeste de los módulos de manera que sigan la posición del sol durante todo el día. Es un sistema idóneo para los sitios de baja latitud. Sin embargo, una de sus limitaciones es que requiere una mayor superficie que el sistema de ángulo fijo (SAF) para una misma potencia. Para aumentar el índice de ocupación del terreno (GCR) desde hace unos años se han desarrollado HSAT con seguimiento retrasado (HSAT-B). Mediante esta tecnología, cuando debiera comenzar el sombreado mutuo de los módulos, el seguimiento se retrasa para evitar el sombreado de la radiación directa. Como Cuba es un pequeño archipiélago con limitaciones de áreas para la instalación de parques fotovoltaicos, los autores comparan esta tecnología con el SAF y con el sistema de doble orientación Este-Oeste (SEO), y concluyen que, ante limitaciones de terreno y de acuerdo a las características del sitio, el seguimiento retrasado es otra alternativa a evaluar.

Multi-hop question answering from knowledge graphs has gained a growing attention in the past few years due to its vast applications in AI. Existing approaches in this regard mostly rely on exhaustively traversing all paths in the graph until reaching a candidate answer entity, leading to high time complexity and reasoning errors when training the model. Recently, a few works have tried to reduce the search space by proposing sequential-decision techniques so that only the path that is likely to lead to the answer is traced. However, the sequential decision on the relations is likely to accumulate errors due to the potential incorrect matching with the question. Alternatively, this work proposes a method that leverages sequence matching and a backtracking algorithm to identify the correct path to the answer while minimizing the accumulated error. The process starts from the question entity and grows the path iteratively by reasoning over the outgoing relations. The aim is to find the relation with the highest similarity to the question and to transit through it to the next entity. Meanwhile, a termination/backtracking check is performed at each iteration to validate the path and act accordingly either by proceeding to the next entity, stopping the process, or backtracking to correct a wrongly expanded path. The proposed method does not require setting a maximum number of hops in advance and uses a compare-aggregate model with attention mechanism for effective sequence matching. Experimental results show that our method significantly outperforms existing methods on three benchmarking datasets.

In the last two years, we have seen a huge number of debates and discussions on COVID-19 in social media. Many authors have analyzed these debates on Facebook and Twitter, while very few ones have considered Reddit. In this paper, we focus on this social network and propose three approaches to extract information from posts on COVID-19 published in it. The first performs a semi-automatic and dynamic classification of Reddit posts. The second automatically constructs virtual subreddits, each characterized by homogeneous themes. The third automatically identifies virtual communities of users with homogeneous themes. The three approaches represent an advance over the past literature. In fact, the latter lacks studies regarding classification algorithms capable of outlining the differences among the thousands of posts on COVID-19 in Reddit. Analogously, it lacks approaches able to build virtual subreddits with homogeneous topics or virtual communities of users with common interests. [ABSTRACT FROM AUTHOR]

Algorithm fundamentals are useful to learn at different levels engineering education. One of the most difficult concepts to teach and understand is backtracking algorithms with proper bounding functions. This article proposes a framework to implement interactive online tools showing examples of backtracking algorithms in which students can graphically observe execution step-by-step. This approach is illustrated with the n-queens problem with students from Prince Sultan University, Saudi Arabia, and Complutense University of Madrid, Spain. The results show 6.67% increased learning on a backtracking exercise in the experimental group over the control group, in which the algorithms were automatically validated with DOMjudge software (an automated system used to run programming contests). The proposed framework was evaluated as easy to use, with a score of 74.5% in the validated System Usability Scale (SUS); easy to learn, with a score of 6.22 out of 7 in the validated Usefulness, Satisfaction, and Ease-of-Use (USE) scale; and with a general satisfaction of 5.97 out of 7 in the validated USE scale. [ABSTRACT FROM AUTHOR]

Inertial odometry is a typical localization method that is widely and easily accessible in many devices. Pedestrian positioning can benefit from this approach based on inertial measurement unit (IMU) values embedded in smartphones. Fitting the inertial odometry outputs, namely step length and step heading of a human for instance, with spatial information is an ubiquitous way to correct for the cumulative noises. This so-called map-matching process can be achieved in several ways. In this paper, a novel real-time map-matching approach was developed, using a backtracking particle filter that benefits from the implemented geospatial analysis, which reduces the complexity of spatial queries and provides flexibility in the use of different kinds of spatial constraints. The goal was to generalize the algorithm to permit the use of any kind of odometry data calculated by different sensors and approaches as the input. Further research, development, and comparisons have been done by the easy implementation of different spatial constraints and use cases due to the modular structure. Additionally, a simple map-based optimization using transition areas between floors has been developed. The developed algorithm could achieve accuracies of up to 3 m at approximately the 90th percentile for two different experiments in a complex building structure. [ABSTRACT FROM AUTHOR]

This paper presents a novel backtracking strategy for additive Schwarz methods for general convex optimization problems as an acceleration scheme. The proposed backtracking strategy is independent of local solvers, so that it can be applied to any algorithms that can be represented in an abstract framework of additive Schwarz methods. Allowing for adaptive increasing and decreasing of the step size along the iterations, the convergence rate of an algorithm is improved. The improved convergence rate of the algorithm is analyzed rigorously. In addition, combining the proposed backtracking strategy with a momentum acceleration technique, we propose a further accelerated additive Schwarz method. Numerical results for various convex optimization problems such as nonlinear elliptic problems, nonsmooth problems, and nonsharp problems are presented in order to support our theory. [ABSTRACT FROM AUTHOR]

Finite control set model predictive control (FCS-MPC) has been widely recognized in the field of electrical drive control during the past decades, due to its merits of quick dynamic response and low switching frequency. However, it is inherently penalized by high tracking deviations in the steady-state as well as exhaustive search among the switching sequences. To cope with this issue, a low-complexity gradient descent-based finite control set predictive current control (GD-FCSPCC) combined with a backtracking iteration approach is proposed in this article, aiming to improve the control performance by effectively tracking the reference value. First, FCS-PCC is reformulated as a quadratic programming (QP) problem from a geometric perspective. Consequently, the convexity of QP problem is proved to underlying the gradient descent, which minimizes the tracking deviations in an effective manner. Thus, the optimal solutions are selected by optimizing the reformulated objective functions. To reduce the number of the searched control inputs, a two-layer generalized decision-tree is employed. The procedures are repeated in several iteration periods optimized via a backtracking method, until the stopping criterion is satisfied. The effectiveness of the proposed GD-FCSPCC is experimentally validated on a 2.2 kW induction machine testbench. [ABSTRACT FROM AUTHOR]

In many cases, initiation is rate limiting to transcription. This due in part to the multiple cycles of abortive transcription that delay promoter escape and the transition from initiation to elongation. Pausing of transcription in initiation can further delay promoter escape. The previously hypothesized pausing in initiation was confirmed by two recent studies from Duchi et al. 1 and from Lerner, Chung et al. 2 In both studies, pausing is attributed to a lack of forward translocation of the nascent transcript during initiation. However, the two works report on different pausing mechanisms. Duchi et al. report on pausing that occurs during initiation predominantly on-pathway of transcript synthesis. Lerner, Chung et al. report on pausing during initiation as a result of RNAP backtracking, which is off-pathway to transcript synthesis. Here, we discuss these studies, together with additional experimental results from single-molecule FRET focusing on a specific distance within the transcription bubble. We show that the results of these studies are complementary to each other and are consistent with a model involving two types of pauses in initiation: a short-lived pause that occurs in the translocation of a 6-mer nascent transcript and a long-lived pause that occurs as a result of 1-2 nucleotide backtracking of a 7-mer transcript.

Initiation is a highly regulated, rate-limiting step in transcription. We used a series of approaches to examine the kinetics of RNA polymerase (RNAP) transcription initiation in greater detail. Quenched kinetics assays, in combination with gel-based assays, showed that RNAP exit kinetics from complexes stalled at later stages of initiation (e.g., from a 7-base transcript) were markedly slower than from earlier stages (e.g., from a 2- or 4-base transcript). In addition, the RNAP-GreA endonuclease accelerated transcription kinetics from otherwise delayed initiation states. Further examination with magnetic tweezers transcription experiments showed that RNAP adopted a long-lived backtracked state during initiation and that the paused-backtracked initiation intermediate was populated abundantly at physiologically relevant nucleoside triphosphate (NTP) concentrations. The paused intermediate population was further increased when the NTP concentration was decreased and/or when an imbalance in NTP concentration was introduced (situations that mimic stress). Our results confirm the existence of a previously hypothesized paused and backtracked RNAP initiation intermediate and suggest it is biologically relevant; furthermore, such intermediates could be exploited for therapeutic purposes and may reflect a conserved state among paused, initiating eukaryotic RNA polymerase II enzymes.

In the literature of Economics, Engineering and Operations Research, the estimation of production frontiers is a current hot topic. Many parametric and nonparametric methodologies have been introduced for estimating technical efficiency of a set of units (for example, firms) from the production frontier. However, few of these methodologies are based upon machine learning techniques, despite being a rising field of research. Recently, a bridge has been built between these literatures, machine learning and production theory, through a new technique proposed in Esteve et al. (2020), called Efficiency Analysis Trees (EAT). The algorithm developed from EAT, based on the well-known Classification and Regression Trees (CART) machine learning technique, is a greedy technique that uses a particular heuristic for the selection of the next node to be split during the decision tree development process. Nevertheless, as we show in this paper, for different sample sizes and number of variables, the heuristic used by EAT is not capable of obtaining the tree with the minimum mean square error (MSE). For this reason, in this paper, a backtracking technique is implemented to improve the MSE obtained by the EAT algorithm. Additionally, a pair of new algorithms are introduced which combine the heuristic technique used by the standard EAT and the backtracking algorithm to enhance the reduction of the MSE, while decreasing the computation time. Our research is based on some simulated experiments. According to our computational results, the combination of the heuristic and the backtracking algorithm, in particular, that in which the tree growth starts with heuristics and ends with backtracking, has achieved an accuracy similar to that of backtracking and within a reasonable computational time. The contribution of the paper could be of special interest for industrial engineers interested in measuring efficiency and productivity of industrial processes in many sectors, such as energy, agri-food or service industries.

Geographical routing is an area of interest for wireless sensor networks because of its scalability and local decision making capability. Usually, geographical routing protocols rely on greedy approach and suffer from the void node problem (VNP). This paper presents an angular three-dimensional routing protocol (A3DR) for wireless sensor networks. In A3DR, the next hop is selected from nodes available in solid angle decided dynamically based on network density, i.e., larger solid angle for sparse networks while a smaller angle for dense one. The delay based contention mechanism has been proposed to select a suitable forwarding node among nodes lying in a particular solid angle. A3DR has a provision to adaptively tune the solid angle to resolve the void node problem. Further, the proposed protocol A3DR will take care of traffic congestion problem suffered by beaconless routing protocol. The A3DR tackle the concave void problem by allowing conditional backtracking to find another suitable path and prevent looping. Additionally, A3DR address overhear problem by utilizing the concept of request-to-forward and clear-to-forward for the nodes lying outside the solid angle 60°. The performance of proposed A3DR is compared with existing protocols by implementing it on the INET framework under OMNET++ simulator. The simulation results indicate that A3DR achieves a high packet reception rate while maximizing the residual energy and minimizing traffic overhead.

Supercomputers and datacenters comprise hundreds of thousands of servers. Different network topologies have been proposed to attain such a high scalability, from flattened Butterfly and Dragonfly to the most disruptive Jellyfish, which is based on a random graph. The routing problem on such networks remains a challenge that can be tackled either as a topology-aware solution or with an agnostic approach. The case of random networks is a very special one since no a priori topological clues can be exploited. In this article, we introduce the polarized routing algorithm, an adaptive nonminimal hop-by-hop mechanism that can be used in most of topologies, including Jellyfish. Polarized routing follows two design criteria: a source–destination symmetry in the routes and avoiding backtracking. Experimental evaluation proves that polarized routing not only outperforms other routings in random graphs but also attains the best performance provided by ad hoc solutions for specific outstanding low-diameter interconnection networks. [ABSTRACT FROM AUTHOR]

Beaches are thought to be a large reservoir for marine plastics. To protect vulnerable beaches, it is advantageous to have information on the sources of this plastic. Here, we develop a universally applicable Bayesian framework to map sources of plastic arriving on a specific beach. In this framework, we combine Lagrangian backtracking simulations of drifting particles with estimates of plastic input from coastlines, rivers and fisheries. The advantage over traditional Lagrangian simulations is that the Bayesian framework can consider information on known sources, and thus facilitates spatiotemporal source attribution for plastic arriving at the specified beach. We show that the main sources for our target beach in southwest Netherlands are the east coast of the UK, the Dutch coast, the English Channel (fisheries) and the Thames, Seine, Rhine and Trieux (rivers). We also show that floating time is a major uncertainty in source attribution using backtracking. Plain Language Summary: A large part of plastic in the ocean is located at or near beaches. This plastic can break down into micro‐plastics or be ingested by animals. Therefore, it is important to clean up these beaches. The easiest way to do so is to prevent the plastic from entering the oceans initially by interfering at the source. In this study, we develop a framework to find these sources for a given beach. We first simulate the path that plastic has taken to reach this beach. We do this by releasing virtual plastic particles at the beach where they end up. Next, we calculate their paths back in time, computing their trajectories until they reach this beach. We then combine these simulations with data on the sources of plastic: where and when did plastic enter the ocean? We apply this framework to a beach in southwest Netherlands, near the town of Domburg. We quantify seasonal effects, where time‐varying currents cause the plastic to come from different sources. Lastly, we study how plastic sources vary with plastic age (the time between the plastic entering the ocean and beaching at its final location). Key Points: Combined oceanic backtracking and Bayesian statistics supports source attribution of beached plasticStrong seasonal variability in likely sources is found, due to variability in plastic input and currentsFloating time remains a major uncertainty in determining the origin of beached plastic via backtracking [ABSTRACT FROM AUTHOR]

Local pseudorandom generators are a class of fundamental cryptographic primitives having very broad applications in theoretical cryptography. Following Couteau et al.’s work at ASIACRYPT 2018, this paper further studies the concrete security of one important class of local pseudorandom generators, i.e., Goldreich’s pseudorandom generators. Our first attack is of the guess-and-determine type. Our result significantly improves the state-of-the-art algorithm proposed by Couteau et al., in terms of both asymptotic and concrete complexity, and breaks all the challenge parameters they proposed. For instance, for a parameter set suggested for 128 bits of security, we could solve the instance faster by a factor of about 277, thereby destroying the claimed security completely. Our second attack further exploits the extremely sparse structure of the predicate $P_{5}$ and combines ideas from iterative decoding. This novel attack, named guess-and-decode, substantially improves the guess-and-determine approaches for cryptographic-relevant parameters. All the challenge parameter sets proposed in Couteau et al.’s work in ASIACRYPT 2018 aiming for 80-bit (128-bit) security levels can be solved in about 258 (278) operations. We suggest new parameters for achieving 80-bit (128-bit) security with respect to our attacks. We also extend the attacks to other promising predicates and investigate their resistance. [ABSTRACT FROM AUTHOR]

The horizontal single-axis tracker system (HSAT) moves collectors changing the East-West orientation to track the sun's position during the day. However, as a limitation, it requires a higher area than the fixed tilt system (SAF) for the same power. Recently, HSAT with backtracking (HSAT-B) has been developed to increase the ground cover ratio (GCR). By backtracking, modules move such that no mutual beam shading occurs. As Cuba is a small country with land constraints for construction of new solar farms, the authors compared the HSAR-B with the SAF and. the East-West orientation system (SEO), and concluded that, facing land restrictions and taking into account the specific characteristics of the site, the backtracking is other technology to assess. [ABSTRACT FROM AUTHOR]

In this paper, we study a well-known computationally hard problem, called the subgraph isomorphism problem where the goal is for a given pattern and target graphs to determine whether the pattern is a subgraph of the target graph. Numerous algorithms for solving the problem exist in the literature and most of them are based on the backtracking approach. Since straightforward backtracking is usually slow, many algorithmic refinement techniques are used in practical algorithms. The main goal of this paper is to study such refinement techniques and to determine their ability to speed up backtracking algorithms. To do this we use a methodology of experimental algorithmics. We perform an experimental evaluation of the techniques and their combinations and, hence, demonstrate their usefulness in practice.

Multiple patterning lithography has been widely adopted in advanced technology nodes of VLSI manufacturing. As a key step in the design flow, multiple patterning layout decomposition (MPLD) is critical to design closure. Due to the $\mathcal {N} \mathcal {P} $ -hardness of the general decomposition problem, various efficient algorithms have been proposed with high-quality solutions. However, with increasingly complicated design flow and peripheral processing steps, developing a high-quality layout decomposer becomes more and more difficult, slowing down further advancement in this field. This article presents $\mathsf {OpenMPL}$ (2020), an open-source layout decomposition framework, with well-separated peripheral processing and core solving steps. Besides, previous algorithms or techniques are inspected and several issues are discovered. We then propose corresponding new algorithms to resolve these issues. The experiments demonstrate the effectiveness of our proposed algorithms and the efficiency of $\mathsf {OpenMPL}$. [ABSTRACT FROM AUTHOR]

A new paradigm has emerged proposing that the crosstalk between nuclear transcription and cytoplasmic mRNA stability keeps robust mRNA levels in cells under steady-state conditions. A key piece in this crosstalk is the highly conserved 5′–3′ RNA exonuclease Xrn1, which degrades most cytoplasmic mRNAs but also associates with nuclear chromatin to activate transcription by not well-understood mechanisms. Here, we investigated the role of Xrn1 in the transcriptional response of Saccharomyces cerevisiae cells to osmotic stress. We show that a lack of Xrn1 results in much lower transcriptional induction of the upregulated genes but in similar high levels of their transcripts because of parallel mRNA stabilization. Unexpectedly, lower transcription in xrn1 occurs with a higher accumulation of RNA polymerase II (RNAPII) at stress-inducible genes, suggesting that this polymerase remains inactive backtracked. Xrn1 seems to be directly implicated in the formation of a competent elongation complex because Xrn1 is recruited to the osmotic stress-upregulated genes in parallel with the RNAPII complex, and both are dependent on the mitogen-activated protein kinase Hog1. Our findings extend the role of Xrn1 in preventing the accumulation of inactive RNAPII at highly induced genes to other situations of rapid and strong transcriptional upregulation. [ABSTRACT FROM AUTHOR]

Pemilihan komputer yang baik adalah menyesuaikan dengan kebutuhan dan ketersediaan anggaran karena hal ini berhubungan dengan spesifikasi perangkat keras di dalamnya. Masih banyak masyarakat awam tidak mempunyai pengetahuan komponen komputer rakitan. Hal ini bias menjadi penyebab kurang optimalnya dalam memilih spesifikasi komputer rakitan berdasarkan kebutuhan dan ketersediaan anggaran. Sehingga perlu adanya suatu sistem yang dapat membantu masyarakat dalam memberikan informasi spesifikasi (komponen-komponen) komputer rakitan yang menyesuaikan dengan kebutuhan dan anggaran yang dimiliki calon pembeli. Pengembangan aplikasi dilakukan dengan mengamati langsung proses pembelian Komputer rakitan yang dilakukan di toko-toko komputer. Selanjutnya melakukan pengumpulan data perangkat keras komputer yang akan dijadikan spesifikasi komputer rakitan. Memilih Algoritma Backtracking dengan teknik Depth First Search dengan fungsi pembatas harga dalam proses penyusunan spesifikasi perangkat keras komputer. Pengujian dilakukan pada 4 komponen hardware untuk Paket Office dengan batas anggaran Rp 5.000.000, dan memperoleh output harga Rp 4.978.000 dengan performa indeks 5482 dan pada Paket Grafik/Game, pengujian dilakukan pada 5 komponen hardware dengan batas anggaran Rp 8.000.000 dan memperoleh 2 pilihan output harga Rp 7.973.000 dan Rp 8.000.000 dengan masing-masing indeks 12749 dan 12373. Kedua pengujian menghasilkan keluaran kombinasi hardware yang tidak melebihi batas anggaran yang dimasukkan.

In-motion alignment of Strapdown Inertial Navigation Systems (SINS) without any geodetic-frame observations is one of the toughest challenges for odometer aided navigation system. It is difficult to obtain an accurate attitude within a short time using coarse alignment under intense maneuvering condition, so one of the main obstacles during in-motion alignment for SINS/OD is to estimate an accurate attitude during fine alignment process under large azimuth misalignment angle. However, most current in-motion alignment methods were based on linear error model. In this paper, an OD aided in-motion alignment method based on backtracking scheme for large misalignment angles is proposed. Three improvements were made as the following: (1) A continuous nonlinear 16-dimensional (16D) SINS/OD error model is derived. (2) We proposed a backtracking-based Extended Kalman filter (EKF) and (3) a strict reverse navigation method is utilized in the backward process. Experimental results illustrated that the proposed method can autonomously improve the estimated attitude accuracy under the condition of large misalignment angle.

Modernization and the ever-increasing trend of introducing modern technologies into various areas of everyday life require school graduates with programming skills. The ability to program is closely related to computational thinking, which is based on algorithmic thinking. It is well known that algorithmic thinking is the ability of students to work with algorithms understood as a systematic description of problem-solving strategies. Algorithms can be considered as a fundamental phenomenon that forms a point of contact between mathematics and informatics. As part of an algorithmic graph theory seminar, we conducted an experiment where we solved the knight’s tour problem using the backtracking method to observe the change in students’ motivation to learn algorithms at a higher cognitive level. Seventy-four students participated in the experiment. Statistical analysis of the results of the experiment confirmed that the use of the algorithm with decision-making in teaching motivated students to learn algorithms with understanding.

Directed self-assembly (DSA) is one of the leading candidates for extending the resolution of optical lithography to sub-7 nm and beyond. By incorporating DSA in multiple patterning lithography (DSA-MP), the flexibility and resolution of contact/via patterning can be further enhanced by using multiple block copolymer (BCP) materials. Prior work faces the dilemma between solution quality and efficiency and is unable to handle 2-D templates. In this article, we capture the essence of template and mask assignment in DSA-MP by a new graph model and a new problem reduction: Our graph model explicitly represents spacing conflict edges and template hyperedges; thus, extra enumeration and manipulation of incompatible via grouping edges can be avoided, and arbitrary 1-D/2-D templates can be natively handled. We further reduce the assignment problem to exact cover, which is encoded by a sparse matrix. Our concise integer linear programming (ILP) formulation and fast backtracking heuristic achieve substantially superior solution quality and efficiency to the state-of-the-art work. Moreover, our problem and graph modelling is flexible and extensible to utilize dummy vias to improve manufacturability. To narrow down the search region of dummy vias, we devise a conflict core finding technique, which is general and applicable to conflict core analysis of exact cover and other multiple patterning layout decomposition problems. Experimental results show the effectiveness and efficiency of our approach. [ABSTRACT FROM AUTHOR]

Immunofixation Electrophoresis (IFE) analysis is of great importance to the diagnosis of Multiple Myeloma, which is among the top-9 cancer killers in the United States, but has rarely been studied in the context of deep learning. Two possible reasons are: 1) the recognition of IFE patterns is dependent on the co-location of bands that forms a binary relation, different from the unary relation (visual features to label) that deep learning is good at modeling; 2) deep classification models may perform with high accuracy for IFE recognition but is not able to provide firm evidence (where the co-location patterns are) for its predictions, rendering difficulty for technicians to validate the results. We propose to address these issues with collocative learning, in which a collocative tensor has been constructed to transform the binary relations into unary relations that are compatible with conventional deep networks, and a location-label-free method that utilizes the Grad-CAM saliency map for evidence backtracking has been proposed for accurate localization. In addition, we have proposed Coached Attention Gates that can regulate the inference of the learning to be more consistent with human logic and thus support the evidence backtracking. The experimental results show that the proposed method has obtained a performance gain over its base model ResNet18 by 741.30% in IoU and also outperformed popular deep networks of DenseNet, CBAM, and Inception-v3. [ABSTRACT FROM AUTHOR]

BackgroundThe statistical study of nuclide track contribution is very important for reactor physics and source term analysis. It is helpful to understand the nuclide transformation paths and the contribution percentage of each path in practical engineering applications to identify important nuclides or nuclear reactions. The nuclide will be usually activated after the material is irradiated by neutrons.PurposeThis study aims to make statistics of nuclide track contribution which is closely related to activation calculation.MethodThe transmutation trajectory analysis method was employed to disassemble the complex reaction network into independent linear chains for analytical calculation, choose to retain the reaction chain while calculating the nuclide stock, and solve the statistical problem of nuclide pathway contribution in activation calculation. First, the transmutation trajectory analysis was searched by the backtracking method. Then, the pathway of the specified nuclide was tracked and the contribution percentage of each path producing the nuclide was obtained. Finally, the nuclide pathway contribution statistical calculation module was developed within the framework of self developed activation program ABURN, and a series of basic problems were tested and verified with comparison of the European activation program FISPACT.ResultThe comparison results show that the nuclide production paths calculated by ABURN are entirely consistent with that of FISPACT, so are the contribution percentage of each path.ConclusionsThe consistent results of ABURN and FISPACT verify that the accuracy of the track contribution statistical research method and program is ensured in this study, and the ABURN program has the functionalities of pathway tracking and contribution statistics.

This paper explores branching vocabulary items as a possible alternative to backtracking in Nanosyntax. Such vocabulary items give rise to the possibility of partial overwrite. Initially, they spell out a node with two phrasal daughters. At a subsequent stage, the right branch is interpreted by a new element, but the original item continues to spell out the left branch of such a derivation. The effects that branching vocabulary items give rise to thus mimic aspects of backtracking, without requiring mechanisms that undo parts of the derivation.

Backtracking, the reverse motion of the transcriptase enzyme on the nucleic acid template, is a universal regulatory feature of transcription in cellular organisms but its role in viruses is not established. Here we present evidence that backtracking extends into the viral realm, where backtracking by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA-dependent RNA polymerase (RdRp) may aid viral transcription and replication. Structures of SARS-CoV-2 RdRp bound to the essential nsp13 helicase and RNA suggested the helicase facilitates backtracking. We use cryo-electron microscopy, RNA-protein cross-linking, and unbiased molecular dynamics simulations to characterize SARS-CoV-2 RdRp backtracking. The results establish that the single-stranded 3' segment of the product RNA generated by backtracking extrudes through the RdRp nucleoside triphosphate (NTP) entry tunnel, that a mismatched nucleotide at the product RNA 3' end frays and enters the NTP entry tunnel to initiate backtracking, and that nsp13 stimulates RdRp backtracking. Backtracking may aid proofreading, a crucial process for SARS-CoV-2 resistance against antivirals. [ABSTRACT FROM AUTHOR]

Solar tracking is an efficient strategy to increase the radiative capture of photovoltaic collectors. Within the multiple efforts made in recent decades to improve the production of these facilities, various works have studied solutions to optimize the number of rotation axes (single or dual rotation axes), the degree of collector coverage, the distances between trackers, the geometric arrangement of trackers or the minimization of shading between collectors. However, although in this type of installation it is common to find collectors with geometric shapes other than rectangles, no studies on the influence of the shape of the collectors on the radiative incidence are found in the literature. In this connection, the present work systematically addresses the study of incident solar radiation in photovoltaic installations with dual-axis trackers with collectors of different geometric shapes. By means of the exhaustive study, the conclusion is drawn that, for dual-axis photovoltaic installations with an optimal tracking strategy, the main variables that influence the annual radiative incidence are the spacing between collectors, the coverage ratio (GCR), and the collector surface, while the type of arrangement of collectors and the shape of these do not show predictive values. [ABSTRACT FROM AUTHOR]

In-motion alignment of navigation-grade strapdown inertial navigation system (SINS) combined with odometer (OD) is one of the challenging issues for the land vehicle navigation, while most current in-motion alignment methods still rely on the measurements of the global positioning system or only aim at improving the attitude alignment, thus neglecting the position alignment. Thus, one of the main obstacles during the in-motion alignment for SINS/OD is to autonomously and simultaneously obtain the high-precision attitude and position within specified time. In this paper, an in-motion alignment scheme based on the backtracking scheme is presented to solve this problem. The proposed method consists of two steps. First, an improved optimization-based coarse alignment (IOBCA) is employed to obtain the attitude and position with reasonable precision, and the gravity deflexion error projection in inertial frame caused by the positioning error is diminished, which contributes to better alignment results for the subsequent process. Second, initialized with the alignment results provided by IOBCA, a backtracking-scheme-based fine alignment combined with the Kalman filter is investigated to make a further improvement in the precision of attitude and position, during which the known initial binding position and zero velocity have been utilized again. The car-mounted field experimental results illustrate that the proposed method can not only autonomously improve the precision of attitude within a short time but also simultaneously achieve the position with high precision.

This article deals with the problem of sequencing $N$ jobs on a single machine with a restrictive common due window. The objective is to minimize the total weighted earliness-tardiness penalties, which conform to just-in-time (JIT) manufacturing. A novel backtracking simulated annealing (BSA) algorithm with a backtracking mechanism and an effective coding scheme is proposed herein to solve this problem. The performance of the proposed BSA algorithm is compared with that of the best available algorithm and the simulated annealing (SA) algorithm using four benchmark problem sets. The computational results reveal that the backtracking mechanism can improve the performance of the SA algorithm and make the proposed BSA algorithm outperform the state-of-the-art algorithm. The proposed BSA algorithm is sufficiently efficient to satisfy the real-world scheduling requirements of the JIT manufacturing system.

This paper describes an interdisciplinary approach to geometry modeling of geospatial boundaries. The objective is to extract surfaces from irregular spatial patterns using differential geometry and obtain coherent directional predictions along the boundary of extracted surfaces to enable more targeted sampling and exploration. Specific difficulties of the data include sparsity, incompleteness, causality and resolution disparity. Surface slopes are estimated using only sparse samples from cross-sections within a geological domain with no other information at intermediate depths. From boundary detection to subsurface reconstruction, processes are automated in between. The key problems to be solved are boundary extraction, region correspondence and propagation of the boundaries via contour morphing. Established techniques from computational physics, computer vision and signal processing are used with appropriate modifications to address challenges in each area. To facilitate boundary extraction, an edge map synthesis procedure is presented. This works with connected component analysis, anisotropic diffusion and active contours to convert unordered points into regularized boundaries. For region correspondence, component relationships are handled via graphical decomposition. FFT-based spatial alignment strategies are used in region merging and splitting scenarios. Shape changes between aligned regions are described by contour metamorphosis. Specifically, local spatial deformation is modeled by PDE and computed using level-set methods. Directional predictions are obtained using particle trajectories by following the evolving boundary. However, when a branching point is encountered, particles may lose track of the wavefront. To overcome this, a curvelet backtracking algorithm has been proposed to recover information for boundary segments without particle coverage to minimize shape distortion.

This article addresses the problem of finding patterns in graphs. This is formally defined as the subgraph isomorphism problem and is one of the core problems in theoretical computer science. We consider the counting variation of this problem. The task is to count all instances of the pattern G occurring in a (usually larger) graph H. The vast majority of algorithms for this problem use a variation of backtracking. Most commonly they exhaustively search through the space of all possible monomorphisms between G and H. The size of the search tree depends heavily on the choice of the ordering of vertices of G, which are systematically assigned to the vertices of H. We use a method called heuristic sampling to estimate the size of the search tree for each ordering in advance. We use this estimation to select the most suitable order of vertices of G which minimizes the expected tree size. This approach is empirically evaluated on a set of instances, showing the practical potential of the method.

Inertial odometry is a typical localization method that is widely and easily accessible in many devices. Pedestrian positioning can benefit from this approach based on inertial measurement unit (IMU) values embedded in smartphones. Fitting the inertial odometry outputs, namely step length and step heading of a human for instance, with spatial information is an ubiquitous way to correct for the cumulative noises. This so-called map-matching process can be achieved in several ways. In this paper, a novel real-time map-matching approach was developed, using a backtracking particle filter that benefits from the implemented geospatial analysis, which reduces the complexity of spatial queries and provides flexibility in the use of different kinds of spatial constraints. The goal was to generalize the algorithm to permit the use of any kind of odometry data calculated by different sensors and approaches as the input. Further research, development, and comparisons have been done by the easy implementation of different spatial constraints and use cases due to the modular structure. Additionally, a simple map-based optimization using transition areas between floors has been developed. The developed algorithm could achieve accuracies of up to 3 m at approximately the 90th percentile for two different experiments in a complex building structure.