Types Of Connections Research Articles

Influence analysis of network evolution on Parrondo effect

Parrondo's paradox is a scheme used to describe an interesting paradoxical situation that a losing Game A and a losing Game B played randomly or periodically will produce a winning result. Here, a dynamic process of network evolution of Link A + Game B is proposed to yield the Parrondo effect. Game B with two asymmetric branches depends on the relative comparison between the capital of the network node and the average capital of all its neighbors. Simulation results demonstrate that network structure evolution make the losing Game B produce a paradoxical effect of winning and would be advantageous to the development of the “ratcheting” mechanism in Game B. Furthermore, the underlying paradoxical mechanism is analyzed to illustrate the parameter space where the “strong” Parrondo effect occurs. Then influence of two types of network connection is analyzed, indicating that the “agitating” effect of the network is basically the same when a node connects to a neighbor's neighbor or randomly chooses a node other than its neighbors. Further, a higher frequency of network evolution yields a larger parameter region where the “strong” Parrondo effect emerges.

Analyzing the Automatic Power Level Control Effect of a Signal Generator in RF Power Sensor Calibration by a Direct Comparison Transfer Method and a Millimeter Wave Application.

Most calibration laboratories prefer the Direct Comparison Transfer Method (DCTM) for a reliable and accurate calibration of power sensors in the radio frequency (RF) scope. Most studies suggest using this calibration method, with its automatic power level control (APLC) of RF signal generators. The APLC is preferred to keep the output power level of the signal generator the same, while the power sensor is calibrated and the reference power sensor is connected to the measurement system. The known APLC mechanisms are also explained for the DCTM, and a comparison of the calibration factor values carried out with and without the automatic power level control process in the DCTM is also given in this study. RF power sensor calibrations with coaxial and waveguide connector types are examined with DCTM in this study as well. This study shows that the DCTM, unless with APLC, should be applied for the waveguide power sensor's calibration at millimeter wave frequencies.

Experimental Study on Seismic Performance of Prefabricated Columns Connected Using a Novel Dry Sleeve

Prefabricated structures are widely used because of their advantages of energy savings, environmental protection, standardization, and universality. However, due to the complex structure of the joints, it is easy to make the joint installation difficult and the prefabricated column connection unreliable, and further lead to the poor seismic performance of the structure. Therefore, a new type of dry sleeve joint with double screw sleeve without support is proposed, and the seismic performance and influencing factors of the new dry-sleeve-joint prefabricated column are studied. This study encompasses seven reinforced concrete columns characterized by cross-sectional dimensions of 600 mm × 600 mm. Among these, five specimens feature a novel dry sleeve connection, while the remaining two specimens were entirely cast-in-place. Low-cycle reversed loading experiments were conducted on all specimens to analyze and compare the damage patterns, hysteresis curves, skeleton curves, displacement ductility, energy dissipation capacity, and ultimate bearing capacity between precast and cast-in-place columns. Several parameters, including fabrication method, axial compression ratio, longitudinal reinforcement diameter, and hoop spacing, were examined. The findings demonstrated that the calculated-to-tested ratio of the ultimate bearing capacity for the prefabricated specimens was determined to be 0.62, indicating a high level of safety. The displacement ductility coefficient for each specimen ranged from 2.43 to 3.31, while the ultimate drift ratio was within the range of 1/41 to 1/33, satisfying the specified requirements for seismic performance. However, the hysteresis curve of the prefabricated specimens exhibited a pinching effect, which may be related to the existence of a weak layer on the joint surface of the post-cast section. In general, the shape of the new dry sleeve is maintained in the test, the connection form can effectively transfer the force, and the longitudinal bars can be strained and yield when the prefabricated column reaches the peak load. The new type of dry sleeve connection can be used for longitudinal reinforcement connection of reinforced concrete columns with seismic design.

A multimodal graph neural network framework for cancer molecular subtype classification

BackgroundThe recent development of high-throughput sequencing has created a large collection of multi-omics data, which enables researchers to better investigate cancer molecular profiles and cancer taxonomy based on molecular subtypes. Integrating multi-omics data has been proven to be effective for building more precise classification models. Most current multi-omics integrative models use either an early fusion in the form of concatenation or late fusion with a separate feature extractor for each omic, which are mainly based on deep neural networks. Due to the nature of biological systems, graphs are a better structural representation of bio-medical data. Although few graph neural network (GNN) based multi-omics integrative methods have been proposed, they suffer from three common disadvantages. One is most of them use only one type of connection, either inter-omics or intra-omic connection; second, they only consider one kind of GNN layer, either graph convolution network (GCN) or graph attention network (GAT); and third, most of these methods have not been tested on a more complex classification task, such as cancer molecular subtypes.ResultsIn this study, we propose a novel end-to-end multi-omics GNN framework for accurate and robust cancer subtype classification. The proposed model utilizes multi-omics data in the form of heterogeneous multi-layer graphs, which combine both inter-omics and intra-omic connections from established biological knowledge. The proposed model incorporates learned graph features and global genome features for accurate classification. We tested the proposed model on the Cancer Genome Atlas (TCGA) Pan-cancer dataset and TCGA breast invasive carcinoma (BRCA) dataset for molecular subtype and cancer subtype classification, respectively. The proposed model shows superior performance compared to four current state-of-the-art baseline models in terms of accuracy, F1 score, precision, and recall. The comparative analysis of GAT-based models and GCN-based models reveals that GAT-based models are preferred for smaller graphs with less information and GCN-based models are preferred for larger graphs with extra information.

Self-centering steel beam-to-column connections with novel superelastic SMA angles

This paper proposed a novel type of self-centering (SC) steel beam-to-column connection using superelastic shape memory alloy (SMA) angles and steel angles. Unlike conventional post-tensioned SC connections, the proposed SC connection utilized SMA angles to provide SC ability and moderate energy dissipation, enabling easy installation and replacement. Experimental and numerical studies were conducted to investigate the cyclic behavior of the connection. Two types of steel connections with different configurations were tested: one equipped with SMA angles only and the other with a combination of SMA and steel angles. The cyclic behavior of the SC steel beam-to-column connections was investigated through a series of experiments. A numerical study was also conducted to provide more insight into the mechanical behavior of the connections and the local strain condition of SMA angles. Numerical results were validated with experimental results. Comparative results demonstrated that both connections exhibited desirable flag-shaped hysteresis behavior with SC and energy dissipation. No obvious damage and residual deformation were observed in SMA angles after cyclic loads in both the experiments and numerical simulations, indicating that the SC connection using SMA angles can be reused for successive mainshocks and aftershocks without replacement. Therefore, the proposed SC connection can help achieve the goal of earthquake resilience in structural design.

Seismic performance analysis of steel frame installed with prefabricated external walls and new connection type

In order to solve the problems existing in prefabricated structure installed with non-structural elements, this paper proposes a new structure type, which is the steel frame installed with prefabricated external wall. Besides, a new connection method is also proposed and designed for this innovative structure type. Based on a specific engineering project, the full-scale pseudo-static cyclic loading test of the steel frame installed with prefabricated external wall (reinforced concrete) is conducted for analyzing the seismic performance of this structural system, which examines the ability of prefabricated external wall to adapt to the deformation of the main structure, the working performance of connection, the damage pattern of the whole structure and the influence of prefabricated wall on the load bearing capacity and stiffness of the main structure. The corresponding numerical simulation by ABAQUS is employed for further investigating the performance of prefabricated external wall and newly proposed connection methods. On the basis of verification about the accuracy of numerical model, the FEA (finite element analysis) models of the detail connection joints with different parameters are established, and the damage distribution, hysteresis curve, skeleton curve and stress distribution are analyzed and compared to explore the influence of the pre-tension force of bolts and thickness of steel plates on the seismic performance of the connections.

Revealing brain connectivity: graph embeddings for EEG representation learning and comparative analysis of structural and functional connectivity.

This study employs deep learning techniques to present a compelling approach for modeling brain connectivity in EEG motor imagery classification through graph embedding. The compelling aspect of this study lies in its combination of graph embedding, deep learning, and different brain connectivity types, which not only enhances classification accuracy but also enriches the understanding of brain function. The approach yields high accuracy, providing valuable insights into brain connections and has potential applications in understanding neurological conditions. The proposed models consist of two distinct graph-based convolutional neural networks, each leveraging different types of brain connectivities to enhance classification performance and gain a deeper understanding of brain connections. The first model, Adjacency-based Convolutional Neural Network Model (Adj-CNNM), utilizes a graph representation based on structural brain connectivity to embed spatial information, distinguishing it from prior spatial filtering approaches dependent on subjects and tasks. Extensive tests on a benchmark dataset-IV-2a demonstrate that an accuracy of 72.77% is achieved by the Adj-CNNM, surpassing baseline and state-of-the-art methods. The second model, Phase Locking Value Convolutional Neural Network Model (PLV-CNNM), incorporates functional connectivity to overcome structural connectivity limitations and identifies connections between distinct brain regions. The PLV-CNNM achieves an overall accuracy of 75.10% across the 1-51 Hz frequency range. In the preferred 8-30 Hz frequency band, known for motor imagery data classification (including α, μ, and β waves), individual accuracies of 91.9%, 90.2%, and 85.8% are attained for α, μ, and β, respectively. Moreover, the model performs admirably with 84.3% accuracy when considering the entire 8-30 Hz band. Notably, the PLV-CNNM reveals robust connections between different brain regions during motor imagery tasks, including the frontal and central cortex and the central and parietal cortex. These findings provide valuable insights into brain connectivity patterns, enriching the comprehension of brain function. Additionally, the study offers a comprehensive comparative analysis of diverse brain connectivity modeling methods.

A Comparison of the Performance of Saltwater Electrolytic Cell Battery with Zinc-Copper and Aluminum-copper Electrodes

Electrical energy is used to drive a non-spontaneous redox reaction in an electrolytic cell battery, which is composed of an electrochemical cell. The process of breaking down chemical compounds through electrolysis is frequently utilized, and it is derived from the Greek word lysis, which means to disintegrate. The electrolytic cell is composed of an electrolyte, two electrodes (one cathode and one anode), and three other components. Water or other solvents are typically used to make an electrolyte, which is a solution that contains dissolved ions. The purpose of this study is to test, analyze, and construct an electrolytic cell battery using various electrolytic solutions, salt-water concentrations, and the integration of fuel cells and electrodes. The research is designed to be experimental and relies on descriptive analysis to assess it. The design focused on the finding the optimal combination of electrode limited to zinc, copper, and aluminum (soda can), different electrolyte, type of connection of the fuel cells and the different concentration of saline solution used in order to provide optimum energy output. According to the data gathered and analyzed, the Zinc-Copper electrode produces an average voltage of 0.705 V per cell. Saltwater electrolyte produces the most effective results based on its cost effectiveness. When saline solution is 30% concentrated, the optimal voltage output is achieved, and fuel cells perform their best when connected in series. Using this parameter, twenty fuel cells are constructed that can produce 14.10 V without any load. The voltage was 7.57 V and the current was 1.1 A when connected to a DC lighting load that has a 12V power supply.

Process-based evaluation of carbon emissions from the on-site construction of prefabricated steel structures: A case study of a multistory data center in China

Prefabricated steel structures are being promoted in China as an important measure to reduce building carbon emissions (CEs). Currently, high-quality carbon emission factors and calculation methods that identify the sources of CEs from construction process are lacking. This study proposed a process-based method for calculating on-site construction CEs and empirically demonstrated its feasibility using a case of a multistory steel structure with typical column-beam systems. Six construction processes comprising 38 subprocesses were first categorized, then the energy and materials consumed for each subprocess were determined to obtain the first-hand CE parameters. The CEs from hoisting the first- and second-section columns were 10.52 kgCO2/column and 14.41 kgCO2/column, respectively, and the CEs from their installation were in the range 38.16–69.18 kgCO2/column. The CEs from hoisting the primary and secondary beams using a car crane were 7.73 kgCO2/beam and 4.52 kgCO2/beam, respectively, with lower CEs of 2.40 kgCO2/beam and 2.22 kgCO2/beam, respectively when a tower crane was used for hoisting. The 14 connection types used to install the primary beams and the 11 connection types used to install the secondary beams had CEs of 13.84–125.96 kgCO2/beam and 10.39–43.49 kgCO2/beam, respectively. The total on-site construction CE was subsequently calculated by summing the CEs from each process. This method was able to track the CE sources for each construction process and their contributions to identify those with high CE intensities. In addition, the case study was evaluated to provide specific feedback on the current national standard for calculating CEs from building construction.

Flexural Behavior of High-Strength Steel and Ultra-High-Performance Fiber-Reinforced Concrete Composite Beams

The flexural performance of steel and concrete composite beams can be further enhanced by utilizing advanced construction materials such as ultra-high performance fiber-reinforced concrete (UHPFRC) and high-strength steel. In this paper, the concept of critical elastic moment resistance is proposed and the equation for its estimation is derived. It was found that the high yield strength of steel calls for a narrow UHPFRC top layer to reach the critical state, whereas this ideal condition is not realistic for composite beams with normal-strength steel and UHPFRC. Small-scale composite beams composed of both high-strength and low-strength steel materials were tested under four-point bending to verify the critical state and performance of different types of connectors. The headed studs and plate connectors were first tested through small-scale push-out tests and then implemented in the composite beam with different spacing. The connection utilizing headed studs with 150 mm spacing performed the best among the three tested specimens in helping reach the critical elastic moment resistance. Finite element analyses of the composite beam were performed based on the estimated material properties under axial and biaxial stress conditions and the results align with the experiment results.

Основные модели именных словосочетаний в мокшанском языке

the article identifies and describes the main models of phrases in which the dominant word is a noun, adjective or adverb, which have received the general name – nominal; the morphological affiliation of the components and a type of connection between them are determined. 17 Bulletin of Ugric Studies. Vol. 14. № 1 (56). 2024. Objective: identification and systematization of the main models of noun phrases in the Moksha language. Research materials: texts from the literary works of the Moksha writers containing different types of phrases. Results and novelty of the research: as a result of the study, structural models of noun phrases in the Moksha language were identified and systematized; phrases were differentiated according to the morphological nature of the main and dependent components. It has been determined that substantive phrases are formed according to seven main models: 1) N ← N, 2) Adj ← N, 3) Pron ← N, 4) Num ← N, 5) Part ← N, 6) Adv ← N (N → Adv ), 7) Inf ← N (N → Inf). In them the main component is expressed by a noun (or substantive), the dependent component is a noun (with or without a postposition), adjective, numeral, pronoun, adverb, participle, infinitive. Adjective phrases are most often formed according to three models: 1) Adj → N (N ← Adj), 2) Adj → Adv (Adv ← Adj), 3) [N.TRANS ← Adj] – the main component is expressed by an adjective, the dependent component is a noun in different case forms or an adverb. Their place in relation to the main component is not regulated. Adverbial phrases are formed according to three main models: 1) Adv ← Adv, 2) Adv ← N (Adv → N), 3) Pron ← Adv (Adv → Pron), where the main component is expressed by an adverb, the dependent component – by an adverb, noun or pronoun. The scientific novelty of the work lies in the fact that in Mordovian linguistics the models of noun phrases in the Moksha language are the subject of research for the first time.

How teachers make connections among ideas in mathematics instruction.

Conceptual understanding involves understanding connections among ideas within a domain. In this chapter, we consider how teachers support students in learning about connections among ideas in mathematics. We review research focusing on teachers' connection making in mathematics classrooms, and we consider several dimensions of variability in that connection making. Across three corpora of lessons that varied in students' grade levels (first grade to college), cultural settings (United States and China), and mathematics content, we found that all teachers produced linking episodes, but the frequency with which they did so varied substantially, raising new questions about the sources and consequences of that variability. Teachers of first-grade students in China routinely engaged their students in co-constructing links; teachers of middle schoolers and college students in the United States typically explained links to students. Linking episodes targeted many different types of connections, including connections between representations, connections between principles and exemplars, connections between procedures and concepts, and connections between concepts and real-world instantiations. Across all three corpora, teachers expressed linked ideas multimodally in a majority of linking episodes. Based on the findings, we present several hypotheses about how teacher behaviors may support students' understanding of connections among ideas, and we suggest directions for future work.

Connections between Theory and Practice of Music in Augustine

This article explores two types of connection between theory and practice of music in Augustinian philosophical thought. On a first account, during the early writings of this African author, especially in the dialogue De Musica, there is a disconnection between musical and the practice of music, in the sense that, while the former leads human beings to the spiritual, the latter fosters us to stay in the material realm. In his later writings, for example, in Enarrationes in Psalm, Augustine describes the practice of music through his sign theory, forming the second account of connection. In such description, he points out that the semantic content of the musical signs is done at the same time, being pragmatic. In this way, the rational encounter of what music actually means is transformed into practice: in the convergence of theory and practice of music. Finally, the article was made as a result of the doctoral research in Philosophy in Complutense University of Madrid.

Study of different connection types in modular composite energy poles and comparison with monolithic reinforced concrete energy poles

Study of different connection types in modular composite energy poles and comparison with monolithic reinforced concrete energy poles

Surge Analysis of Air Vessel with Different Connection Types in Pressurized Water Delivery Systems

Surge Analysis of Air Vessel with Different Connection Types in Pressurized Water Delivery Systems

The role of technology in shaping the coexistence of local hospital buildings

Architecture is one of the reflections of the development of societies and an indication of the extent of their development from the technological aspect, as this results in products characterized by uniqueness and positivity, as the role of technology is highlighted in the occurrence of symbiotic interference on existing buildings, especially hospital buildings, because this type of building has a constant need for expansion, so the relationship between the origin and the symbiont differs. Depending on the time of addition and the subsequent technological developments that give possibilities and possibilities for coexistence, in addition to the factor of the surrounding environment, the general fabric, and the original building, the important role in determining patterns for reconfiguration of coexistence. However, the concept of technology has the fundamental role in determining the type of relationship and connection and its degree between two cities, as the research aims to clarify the perception. Knowledge about the impact of technology on existing local hospital buildings in terms of materials, structures and mechanisms used when merging old and new, and applying the theoretical framework that has been reached on two samples of existing local hospitals and showing how to achieve the coexistence formation of this type of building to arrive at the most important conclusions (developments affect Technology on hospital configurations when adding and expanding, especially at the levels (structures - materials - facades - basic composition)).

Ensaios de push-out: conexões por aderência no contexto de lajes treliçadas

Abstract Composite structures and precast solutions stand out because they lead to simple, fast erected and economic constructions. In steel-concrete composite construction, shear connectors are used to assure the shear transfer between the steel profile and the concrete slab, enabling the composite action to develop. This paper discusses an innovative technology for connection by adherence, whose resistance is due to friction on various steel-concrete interfaces. The authors consider that this type of shear connection is suitable for composite beams with latticed joists slabs, and the study developed intends to analyze the behavior of the proposed connection, in this application's context, through experimental and numerical approaches. For this purpose, push-out specimens were fabricated and tested in accordance with Eurocode-4 requirements, where the connection behavior is analyzed in terms of its load-slip relation, and the failure modes are identified. Experimental and numerical results allowed to induce that the connector by adherence made with a checkered steel plate is appropriate to be used in composite structures, as it exhibits satisfactory shear resistance and ductility performance. Also, specimens with latticed joist slabs presented average load capacity values with the same magnitude as the average load capacity obtained in models with solid slabs, despite being more prone to cracking. From the parametric study, an increase of 100% in the connector height implied strength increase from 16% to 25%, depending on slab type.

Field test of compactability of soaked subsidence soil using heavy tamper

Dynamic compaction, including heavy compaction, is a widespread method throughout the world for improving the physical and mechanical characteristics of subsidence and low-density soils. The results of theoretical and experimental studies have established that the depth of compaction and the density of compacted soils depend on the weight, shape of the bottom, the height of the tamper and humidity, the type of structural connection, and the granulometric composition of the compacted soil. This article discusses the results of compaction with a heavy tamper when soaking loess-like subsidence soil, widespread in the city of Darkhan, Mongolia, to optimal moisture.

Особенности семантических отношений стимулов и реакций в ассоциативной деятельности учебных билингвов

The article examines the type of semantic connections between stimuli and responses shown during free association in an experimental situation with the participation of educational bilinguals — Chinese students studying Russian. It was assumed that the predominance of certain methods of response in educational bilinguals is due not only to the syntactic connections of words of different parts of speech, but also to a greater or lesser breadth of mastery of the syntagmatic and paradigmatic relations of units of the language being studied. Analysis of the results of the associative experiment in the aspect of classifying semantic relations with stimuli showed the highest frequency in any associative field of the deployment reaction, which is associated with the dominance of the tactic of “attributing a sign to an object”, as well as with the educational nature of bilinguism — foreign speakers reproduce the syntax (S — R) used by them in Russian language classes in various exercises and texts.

Decoding Human Somatosensory Sensitivity Through Resting EEG and Behavioral Analysis: A Multimodal Fusion Approach.

In precision medicine and clinical pain management, the creation of quantitative, objective indicators to assess somatosensory sensitivity was essential. This study proposed a fusion approach for decoding human somatosensory sensitivity, which combined multimodal (quantitative sensory test and neurophysiology) features to classify the dataset on individual somatosensory sensitivity and reveal distinct types of brain activation patterns. Sixty healthy participants took part in the experiment on somatosensory sensitivity that implemented cold, heat, mechanical punctate, and pressure stimuli, and the resting-state electroencephalography (EEG) was collected using BrainVision. The quantitative sensory testing (QST) scores of the participants were clustered using the unsupervised k-means algorithm into four subgroups: generally hypersensitive (HS), generally non-sensitive (NS), predominantly thermally sensitive (TS), and predominantly mechanically sensitive (MS). Furthermore, two types of power spectral density (PSD), band-based PSD (BB-PSD) and frequency-based PSD (FB-PSD), and two types of inter-electrode connectivity (IEC), band-based connectivity (BBC) and frequency-based connectivity (FBC), derived from resting-state EEG were subjected to feature selection with a proposed prior-compared minimum-redundancy maximum-relevance (PCMRMR) protocol. Their effectiveness was then tested by the supervised classification tasks using support vector machine (SVM), k-nearest neighbor (kNN), random forest (RF), and Gaussian classifier (GC). Brain networks of four somatosensory types were revealed by decoding fused multimodal data, namely type-averaged connectivity. The data from sixty healthy individuals were divided into training (n =59) and validation (n =1) datasets according to leave-one-subject-out (LOSO) criteria. The FBC was identified, which can serve as better brain signatures than BB-PSD, FB-PSD, and BBC to classify subjects as HS, NS, TS, or MS groups. Using the SVM, kNN, RF, and GC models, the best accuracy of 87% was obtained when classifying participants into HS, NS, TS, or MS groups. Moreover, the brain networks were decoded from HS, NS, TS, and MS groups by decoding the type-averaged connectivity fused from somatosensory phenotypes and selected FBC. It indicated that quantified multi-parameter somatosensory sensitivity could be achieved with acceptable accuracy, leading to considerable possibilities for using objective pain perception evaluation in clinical practice.