Step In Construction Research Articles

An efficient implementation of graph-based invariant set algorithm for constrained nonlinear dynamical systems

The graph-based invariant set (GIS) algorithm is a promising set-based technique for computing the largest (with respect to inclusion) control invariant set of general discrete-time nonlinear dynamical systems. However, like other invariant set algorithms for nonlinear systems, the GIS algorithm may require a lot of resources when computing the control invariant set. This limits its applicability to higher dimensional systems. In this work, we present an improved and efficient implementation of the GIS algorithm for general discrete-time controlled nonlinear systems. We first identify the bottlenecks through extensive analysis, and then provide remedial procedures to improve the implementation of the GIS algorithm. Specifically, we developed an adaptive subdivision scheme using a supervised machine learning-based algorithm to reduce the cell growth rate and parallelize the graph construction step. We extensively demonstrate the performance of the improved GIS algorithm using a numerical example and compare the result to that of the standard GIS algorithm. The results show that the adaptive subdivision and the parallelization improved the speed of the algorithm by about 8x and 3x respectively, that of the standard GIS algorithm.

Designing a Human-in-the-Loop System for Object Detection in Floor Plans

In recent years, companies in the Architecture, Engineering, and Construction (AEC) industry have started exploring how artificial intelligence (AI) can reduce time-consuming and repetitive tasks. One use case that can benefit from the adoption of AI is the determination of quantities in floor plans. This information is required for several planning and construction steps. Currently, the task requires companies to invest a significant amount of manual effort. Either digital floor plans are not available for existing buildings, or the formats cannot be processed due to lack of standardization. In this paper, we therefore propose a human-in-the-loop approach for the detection and classification of symbols in floor plans. The developed system calculates a measure of uncertainty for each detected symbol which is used to acquire the knowledge of human experts for those symbols that are difficult to classify. We evaluate our approach with a real-world dataset provided by an industry partner and find that the selective acquisition of human expert knowledge enhances the model’s performance by up to 10.5%—resulting in an overall prediction accuracy of 92.1% on average. We further design a pipeline for the generation of synthetic training data that allows the systems to be adapted to new construction projects with minimal manual effort. Overall, our work supports professionals in the AEC industry on their journey to the data-driven generation of business value.

BIM-based estimation of inputs for site layout planning and locating irregularly shaped facilities

Although construction site layout planning (CSLP) is a significant step in construction planning that has a direct impact on the project performance, its input parameters are mainly obtained by asking site managers and related contractors. The dynamic environment, complexities, and uncertainties of a construction project cause a reduction in the precision of these inputs. This study aims to enhance the CSLP precision by providing a holistic and practical method for estimating these parameters. For this intention, a database is established using the data obtained from the project schedule and BIM to allow the calculation of the input parameters. A new algorithm for facility setup is also proposed for optimizing the facility's shape, which seems beneficial in congested sites where space becomes a limited resource. A case study demonstrates the practicality and functionality of the method. The facility setup algorithm also causes an improvement over restricting facilities to regular shapes.

Structural rigidity theory applied to the scaffold-free (dis)assembly of space frames using cooperative robotics

This paper presents a fabrication-informed design method for triangulated space frame structures that remain stable during all phases of their robotic assembly and disassembly without requiring external scaffolding. A graph theoretic framework, based on rigidity theory, is developed to allow the structure, its support conditions, and the impact of robotic support constraints to be simultaneously represented in a single topological framework. The structural system is sequentially designed with an assembly logic based on Henneberg graph-construction steps, which are executed with two robots through a cooperative rigidity-preserving sequence. Ensuring planarity of the resulting graph during these construction steps is shown to lead to intrinsic disassembly potentials within the system. A graph-based algorithm is presented to locate, isolate and remove locally rigid tetrahedral cells formed in the structural system. This algorithm is then utilized to compute a rigidity-preserving robotic disassembly sequence. The design method is demonstrated in the case study design of a wooden space frame arch structure that is robotically (dis)assembled.

Rural Planning Evaluation Based on Artificial Neural Network.

The continuation of human civilization is inseparable from the development and construction of rural areas, and infrastructure is the core of rural development. China has been building large-scale rural infrastructure in recent years. Rural infrastructure building, for example, is huge in both quantity and scope, but it is beset by challenges in its current construction and development, and it urgently requires suitable leadership. Planning assessment, as a technical method, can identify problems in regional development and is a powerful tool for evaluating the impact of planning and construction and promoting the development of complete new areas. This paper is aimed at the planning evaluation of rural construction and the evaluation of rural construction and guides the planning and implementation of the next step of rural construction, to assist China's supervision and inspection of rural construction effect and promote rural construction and development into a good track. In view of the low accuracy and efficiency of the current evaluation model of rural planning and the problem that a single neural network easily produces local extreme value, the neural network method is improved, and the application of LM-BP neural network in the evaluation model of rural planning is proposed. Input sample elements are five factors affecting rural construction, including industrial construction, population distribution, and utilization rate of large-scale facilities, construction of public facilities, and promotion effect of supporting policies. Output sample is the evaluation result. On this foundation, the LM-BP neural network was used to convert the training into a least square problem, and the LM method was used to redefine the number of hidden layer nodes, resulting in the construction of a rural planning evaluation model based on the LM-BP neural network. This approach is used to determine the outcomes of rural planning evaluations. The experimental results show that the designed evaluation model has a small evaluation error, has the advantage of high accuracy compared with similar models, and is a reliable evaluation model for rural planning.

Metal/Metal Dual Catalysis in C−H Activation

AbstractMetal/metal dual catalysis provides new viewpoints and opportunities for C−H functionalization, especially in reactivity and selectivity control aspects. It helps to realize sequential or cooperative catalytic transformations in one‐pot, shortening the synthetic steps in target molecules construction. This micro‐review summarizes the most recent advances in this research field, discusses related mechanism, collecting examples according to the role of the metal species.

Seismic vulnerability analysis of simply supported continuous bridge during construction

PurposeIn order to explore the damage probability of bridge engineering in the event of earthquake in the construction stages, the analysis method of seismic vulnerability in the construction stages is proposed in this paper.Design/methodology/approachBased on the joint simulation function of construction stage conditions and seismic response conditions of MIDAS/Civil finite element analysis software, combined with the method of IDA analysis and compared the relationship between demand and capacity.FindingsThe research shows that: (1) the average seismic loss in different construction stages varies greatly; (2) the seismic vulnerability varies greatly in different construction stages. The vulnerability of the bridge in stage 6 is determined by the longitudinal direction of bridge. Therefore, during the construction of the whole bridge, we should focus on strengthening the disaster and loss prevention strategy of earthquake insurance in the longitudinal direction of bridge. (3) The application of the secondary dead load mainly affects the fragilityin the longitudinal direction of bridge, but has little effect on the fragility in the transversal direction of bridge.Originality/valueThis paper is to explore the seismic vulnerability of a typical simply supported continuous bridge during the construction stages, and to trace the entire construction stage of a typical simply supported continuous bridge. According to the characteristics of the system transformation in the actual construction steps, demand-capacity ratios were established based on incremental dynamic analysis (IDA) and performance indicators of moment curvature and stability, and the seismic vulnerability research is carried out for the construction stages prone to earthquake damage. Furthermore, it provides a basis for seismic risk assessment of such bridges in different construction stages.

Partial event coincidence analysis for distinguishing direct and indirect coupling in functional network construction

Correctly identifying interaction patterns from multivariate time series presents an important step in functional network construction. In this context, the widespread use of bivariate statistical association measures often results in a false identification of links because strong similarity between two time series can also emerge without the presence of a direct interaction due to intermediate mediators or common drivers. In order to properly distinguish such direct and indirect links for the special case of event-like data, we present here a new generalization of event coincidence analysis to a partial version thereof, which is aimed at excluding possible transitive effects of indirect couplings. Using coupled chaotic systems and stochastic processes on two generic coupling topologies (star and chain configuration), we demonstrate that the proposed methodology allows for the correct identification of indirect interactions. Subsequently, we apply our partial event coincidence analysis to multi-channel EEG recordings to investigate possible differences in coordinated alpha band activity among macroscopic brain regions in resting states with eyes open (EO) and closed (EC) conditions. Specifically, we find that direct connections typically correspond to close spatial neighbors while indirect ones often reflect longer-distance connections mediated via other brain regions. In the EC state, connections in the frontal parts of the brain are enhanced as compared to the EO state, while the opposite applies to the posterior regions. In general, our approach leads to a significant reduction in the number of indirect connections and thereby contributes to a better understanding of the alpha band desynchronization phenomenon in the EO state.

Construction of heterogeneous medical knowledge graph from electronic health records

Knowledge graph (KG) is a knowledge organization that enables the users to quickly and accurately query the information required. It is stored in the form of triples. It finds its application in various fields of enterprises, academics, medical etc. In this paper, Medical Knowledge Graph is constructed from Electronic Health Records (EHR) that maps the relationships between the entities of patients, disease and drugs. The heterogeneous graph is constructed using different entities derived from distinct datasets and the information is extracted in the form of queries among the wide between the quantity demand and the wide variety of variables. The steps for construction of Medical Knowledge Graph are data collection, Named entity recognition, entity normalization, entity ranking, and Graph Neural Networks. The hybrid approach of Bi-directional Long Short-Term Memory Multi-Head Attention Conditional Random Field (BILSTM-MULATT-CRF) is used for Named Entity Recognition and the result of Precision 91.4%, Recall 90.15% and F1 score 90.77% is obtained.

Characteristics of Dynamic Safety Factors during the Construction Process for a Tunnel-Group Metro Station

Dynamic safety factors during the construction of an overlapping tunnel-group metro station were studied in the framework of the strength-reduction finite element method. Based on the equivalent plastic strain and displacement of surrounding rock, its damage mode under typical excavation conditions was investigated. The aim of this investigation was to provide information for the design activities concerning the supporting system of the station and the pre-reinforcement of its surrounding ground. The accuracy of the model was assessed by comparing the ground settlements obtained from on-site monitoring with those from the numerical model. The analysis results show that the safety factor reaches the minimum when the No. 3 guide hole of the station hall is excavated. Thus, this is the most dangerous construction step. During this step, the plastic zone penetration phenomenon occurs in the surrounding rock, which is sandwiched between the hall and the platform of the station. In this case, both the deformation of the surrounding rock and the internal forces of the lining increase. The surrounding rock in the sidewall loses its stability. Thereafter, the primary support plays a role of stabilizing the guide hole.

Characterization of Enzymes Catalyzing the Initial Steps of the β-Lactam Tabtoxin Biosynthesis

Tabtoxin is a β-lactam ring-containing phytotoxin produced by a plant pathogenic Pseudomonas species. Here, we describe the early stages of tabtoxin biosynthesis, involving a C-methylation reaction catalyzed by the S-adenosyl-l-methionine-dependent methyltransferase TblA as the initial step for the β-lactam construction. Gene deletion and in vitro biochemical assays demonstrated that the Gcn5-related N-acetyltransferase domain of TblD catalyzes the acetylation of the α-amino group of 5-methyl-l-lysine. This establishment of the early reaction steps lays the foundation for characterizing unique β-lactam biosynthesis.

Construction of cognitive skills test of Textiles

This study was conducted to construct a reliable and valid test in Textiles named as the Cognitive Skills Test of Textiles (CSTT) to measure the effect of teaching instructions on six basic cognitive skills. The important steps of test construction followed by the researchers are planning, preparation of test items (content analysis and blue print), try outs, item analysis, reliability and validity. After try outs and item analysis only 60 items covering 10 questions on each basic cognitive skill remained in the final form of test. It was observed during try-outs that 10 minutes are sufficient to fill the general information part and review the test while 1 minute is enough to attempt one item. Researchers finally decided to provide 75 minutes for completion of the test to err on the side of caution. The answer sheets were scored with the help of scoring key which was prepared by the investigator. Each correct answer was awarded one mark and incorrect was awarded zero.Test was further standardized by experimental validation that included establishing reliability and validity. Product moment method of correlation was applied to calculate coefficient of correlation which was treated as reliability of half test and it was found to be 0.79. To calculate the reliability Spearman-Brown Prophecy formula was used and it was found to be 0.88. Therefore, the test is found highly reliable. Content validity was established, in terms of consistency of test items with objectives as well as content, by giving the test to 20 subject experts in degree colleges. The experts agreed with the investigator with the distribution of content and objective of the content as well as with the scoring procedure.

Tahapan Konstruksi dan Logika Struktur Rumah Adat Sa’o di Dusun Doka, Nusa Tenggara Timur

<p class="Abstract"><em>Traditional architecture in Doka called Sa’o (traditional house) has a unique physical identity in the form of structure and construction. Even though it looks simple, the structure of the foundation, the body, and the roof is able to provide strength and stability to the building. If we are looking back to see how to build a traditional house in the past, the trial and error strategy becomes a method of logical thinking by understanding the principles of building structures. For this reason, this study aims to determine the logical thinking of structural principles by identifying all steps of construction and every structural element obtained through field observations. The results show that the form of structure and construction steps at the traditional house (Sa’o) has considered the principle of load distribution and the response to the styles that influence it. That’s why this research became more interesting as a knowledge to understand the logic of thinking of those people while creating an architectural concept.</em></p>

Implementing Reading to Learn (R2L) Pedagogy to Help Indonesian Junior High School Students Generate News Report Text

The Reading to Learn (R2L) pedagogy, which requires preparing for reading, detailed reading, joint construction, and independent construction steps, was invented in Australia to assist Australian indigenous secondary school students in reading texts and finding useful information inside the texts. This one group pre-test and post-test design was aimed at unfolding the effectiveness of R2L pedagogy in helping the students in constructing well-structured news report texts. A total of 51 ninth-grade students from a junior high school, Bandung, Indonesia participated in the research. The students received the R2L pedagogy in four meetings within a month, excluding the pre-test and post-test.

Arboreal wildlife bridges in the tropical rainforest of Costa Rica’s Osa Peninsula

Abstract Linear infrastructures, especially roads, affect the integrity of natural habitats worldwide. Roads act as a barrier to animal movement, cause mortality, decrease gene flow and increase the probability of local extinctions, particularly for arboreal species. Arboreal wildlife bridges increase connectivity of fragmented forests by allowing wildlife to safely traverse roads. However, the majority of studies about such infrastructure are from Australia, while information on lowland tropical rainforest systems in Meso and South America remains sparse. To better facilitate potential movement between forest areas for the arboreal wildlife community of Costa Rica’s Osa Peninsula, we installed and monitored the early use of 12 arboreal wildlife bridges of three different designs (single rope, double rope, and ladder bridges). We show that during the first 6 months of monitoring via camera traps, 7 of the 12 bridges were used, and all bridge designs experienced wildlife activity (mammals crossing and birds perching). A total of 5 mammal species crossing and 3 bird species perching were observed. In addition to preliminary results of wildlife usage, we also provide technical information on the bridge site selection process, bridge construction steps, installation time, and overall associated costs of each design. Finally, we highlight aspects to be tested in the future, including additional bridge designs, monitoring approaches, and the use of wildlife attractants.

Lactate biosensing based on covalent immobilization of lactate oxidase onto chevron-like graphene nanoribbons via diazotization-coupling reaction

We have designed and prepared an electrochemical biosensor for lactate determination. Through a diazotation process, the enzyme lactate oxidase (LOx) is anchored onto chevron-like graphene nanoribbons (GNR), previously synthesized by a solution-based chemical route, and used as modifiers of glassy carbon electrodes. In a first step, we have performed the grafting of a 4-carboxyphenyl film, by electrochemical reduction of the corresponding 4-carboxyphenyl diazonium salt, on the GNR-modified electrode surface. In this way, the carboxylic groups are exposed to the solution, enabling the covalent immobilization of the enzyme through the formation of an amide bond between these carboxylic groups and the amine groups of the enzyme. The biosensor design was optimized through the morphological and electrochemical characterization of each construction step by atomic force microscopy, scanning electron microscopy, cyclic voltammetry and electrochemical impedance spectroscopy.The cyclic voltammetric response of the biosensor in a solution of hydroxymethylferrocene in presence of l-lactate evidenced a clear electrocatalytic effect powered by the specific design of the biosensing platform with LOx covalently attached to the GNR layer. From the calibration procedures employed for l-lactate determination, a linear concentration range of 3.4 · 10−5– 2.8 · 10−4 M and a detection limit of 11 μM were obtained, with relative errors and relative standard deviations less than 6.0% and 8.4%, respectively. The applicability of the biosensor was tested by determining lactate in apple juices, leading to results that are in good agreement with those obtained with a well-established enzymatic spectrophotometric assay kit.

Analysis of Trend Culture from the Perspective of Social Currency

Under the wave of consumerism, "blind box play" quickly swept the world and became the darling of young people's trend consumption. This article takes the hot sale of "blind box" as an example, and believes that the product has accumulated users, expanded its influence, formed a community in the network ecology, and finally completed the construction of a communication path. This paper also attempts to find out the advantages for reference in the current media product marketing in the analysis of the construction steps of "social currency", and proposes a directional reference for the development path of the new ecological community economy.

Optimized assay for transposase-accessible chromatin by sequencing (ATAC-seq) library preparation from adult Drosophila melanogaster neurons

Assay for transposase-accessible chromatin by sequencing (ATAC-seq) is rapidly becoming the assay of choice to investigate chromatin-mediated gene regulation, largely because of low input requirements, a fast workflow, and the ability to interrogate the entire genome in an untargeted manner. Many studies using ATAC-seq use mammalian or human-derived tissues, and established protocols work well in these systems. However, ATAC-seq is not yet widely used in Drosophila. Vinegar flies present several advantages over mammalian systems that make them an excellent model for ATAC-seq studies, including abundant genetic tools that allow straightforward targeting, transgene expression, and genetic manipulation that are not available in mammalian models. Because current ATAC-seq protocols are not optimized to use flies, we developed an optimized workflow that accounts for several complicating factors present in Drosophila. We examined parameters affecting nuclei isolation, including input size, freezing time, washing, and possible confounds from retinal pigments. Then, we optimized the enzymatic steps of library construction to account for the smaller Drosophila genome size. Finally, we used our optimized protocol to generate ATAC-seq libraries that meet ENCODE quality metrics. Our optimized protocol enables extensive ATAC-seq experiments in Drosophila, thereby leveraging the advantages of this powerful model system to understand chromatin-mediated gene regulation.

Switchable DNA-Encoded Chemical Library: Interconversion between Double- and Single-Stranded DNA Formats.

DNA-encoded chemical libraries (DEL) have attracted substantial attention due to the infinite possibility for hit discovery in both pharmaceutical companies and academia. The encoding method is the initial step of DEL construction and one of the cornerstones of DEL applications. Classified by the DNA format, the existing DEL encoding strategies were categorized into single-stranded DNA-based strategies and double-stranded DNA-based strategies. The two DEL formats have their unique advantages but are usually incompatible with each other. To address this issue, we propose the concept of interconversion between double- and single-stranded DEL based on the "reversible covalent headpiece (RCHP)" design, which combines maximum robustness of synthesis with extraordinary flexibility of applications in distinct setups. Future opportunities in this field are also proposed to advance DEL technology to a comprehensive drug discovery platform.

The GRN concept as a guide for evolutionary developmental biology.

Organismal phenotypes result largely from inherited developmental programs, usually executed during embryonic and juvenile life stages. These programs are not blank slates onto which natural selection can draw arbitrary forms. Rather, the mechanisms of development play an integral role in shaping phenotypic diversity and help determine the evolutionary trajectories of species. Modern evolutionary biology must, therefore, account for these mechanisms in both theory and in practice. The gene regulatory network (GRN) concept represents a potent tool for achieving this goal whose utility has grown in tandem with advances in "omic" technologies and experimental techniques. However, while the GRN concept is widely utilized, it is often less clear what practical implications it has for conducting research in evolutionary developmental biology. In this Perspective, we attempt to provide clarity by discussing how experiments and projects can be designed in light of the GRN concept. We first map familiar biological notions onto the more abstract components of GRN models. We then review how diverse functional genomic approaches can be directed toward the goal of constructing such models and discuss current methods for functionally testing evolutionary hypotheses that arise from them. Finally, we show how the major steps of GRN model construction and experimental validation suggest generalizable workflows that can serve as a scaffold for project design. Taken together, the practical implications that we draw from the GRN concept provide a set of guideposts for studies aiming at unraveling the molecular basis of phenotypic diversity.