Block Model Research Articles

Monitoring networks with overlapping communities based on latent mixed-membership stochastic block model

Monitoring networks with overlapping communities based on latent mixed-membership stochastic block model

Characterizing phonemic fluency by transfer learning with deep language models.

Though phonemic fluency tasks are traditionally indexed by the number of correct responses, the underlying disorder may shape the specific choice of words-both correct and erroneous. We report the first comprehensive qualitative analysis of incorrect and correct words generated on the phonemic ('S') fluency test, in a large sample of patients (n = 239) with focal, unilateral frontal or posterior lesions and healthy controls (n = 136). We conducted detailed qualitative analyses of the single words generated in the phonemic fluency task using categorical descriptions for different types of errors, low-frequency words and clustering/switching. We further analysed patients' and healthy controls' entire sequences of words by employing stochastic block modelling of Generative Pretrained Transformer 3-based deep language representations. We conducted predictive modelling to investigate whether deep language representations of word sequences improved the accuracy of detecting the presence of frontal lesions using the phonemic fluency test. Our qualitative analyses of the single words generated revealed several novel findings. For the different types of errors analysed, we found a non-lateralized frontal effect for profanities, left frontal effects for proper nouns and permutations and a left posterior effect for perseverations. For correct words, we found a left frontal effect for low-frequency words. Our novel large language model-based approach found five distinct communities whose varied word selection patterns reflected characteristic demographic and clinical features. Predictive modelling showed that a model based on Generative Pretrained Transformer 3-derived word sequence representations predicted the presence of frontal lesions with greater fidelity than models of native features. Our study reveals a characteristic pattern of phonemic fluency responses produced by patients with frontal lesions. These findings demonstrate the significant inferential and diagnostic value of characterizing qualitative features of phonemic fluency performance with large language models and stochastic block modelling.

BrickStARt: Enabling In-situ Design and Tangible Exploration for Personal Fabrication using Mixed Reality

3D-printers enable end-users to design and fabricate unique physical artifacts but maintain an increased entry barrier and friction. End users must design tangible artifacts through intangible media away from the main problem space (ex-situ) and transfer spatial requirements to an abstract software environment. To allow users to evaluate dimensions, balance, or fit early and in-situ, we developed BrickStARt, a design tool using tangible construction blocks paired with a mixed-reality headset. Users assemble a physical block model at the envisioned location of the fabricated artifact. Designs can be tested tangibly, refined, and digitally post-processed, remaining continuously in-situ. We implemented BrickStARt using a Magic Leap headset and present walkthroughs, highlighting novel interactions for 3D-design. In a user study (n=16), first-time 3D-modelers succeeded more often using BrickStARt than Tinkercad. Our results suggest that BrickStARt provides an accessible and explorative process while facilitating quick, tangible design iterations that allow users to detect physics-related issues (e.g., clearance) early on.

Linear Factor Analytic Thurstonian Forced-Choice Models: Current Status and Issues.

Thurstonian forced-choice modeling is considered to be a powerful new tool to estimate item and person parameters while simultaneously testing the model fit. This assessment approach is associated with the aim of reducing faking and other response tendencies that plague traditional self-report trait assessments. As a result of major recent methodological developments, the estimation of normative trait scores has become possible in addition to the computation of only ipsative scores. This opened up the important possibility of comparisons between individuals with forced-choice assessment procedures. With item response theory (IRT) methods, a multidimensional forced-choice (MFC) format has also been proposed to estimate individual scores. Customarily, items to assess different traits are presented in blocks, often triplets, in applications of the MFC, which is an efficient form of item presentation but also a simplification of the original models. The present study provides a comprehensive review of the present status of Thurstonian forced-choice models and their variants. Critical features of the current models, especially the block models, are identified and discussed. It is concluded that MFC modeling with item blocks is highly problematic and yields biased results. In particular, the often-recommended presentation of blocks with items that are keyed in different directions of a trait proves to be counterproductive considering the goal to reduce response tendencies. The consequences and implications of the highlighted issues are further discussed.

Spatio-temporal evolution laws of storage coefficient of coal mine underground reservoir and contact network of crushed rock.

Spatio-temporal evolution laws of storage coefficient and contact network of crushed rock are of great significance for the construction and utilization of underground reservoirs in coal mines. Based on discrete element method and irregular rigid block model, spatio-temporal evolution laws of storage coefficient and contact network of crushed rock under different overburden stresses are investigated and the following main conclusions are obtained: (1) The average storage coefficient and the storage coefficient at different vertical heights of the crushed rock packing system decrease exponentially as the overburden stress increases. When the overburden stress ranges from 0 to 20 MPa, the average storage coefficient decreases by 48.947%. (2) The average void radius and throat radius of water storage space decrease exponentially as the overburden stress increases. The increase in overburden stress leads to the transformation of large voids into smaller voids, causing a gradual decrease in void connectivity and a tendency towards irregular void shapes. (3) With the increase of overburden stress, the number of strong contacts in the packing system of crushed rock increases and gradually expands from the top to the bottom. The average contact force of crushed rock increases exponentially, while the coordination number increases linearly. (4) As the overburden stress increases, the majority of contact directions are concentrated within the ±30° range in the loading direction. This increase results in an enhancement of the anisotropy of the packing system structure of crushed rock.

Mathematical Modeling of a Three-Phase Induction Motor Fed by a Photovoltaic System

This paper presents the mathematical modeling of the three-phase squirrel cage induction motor and its driver, the DC bus, and a photovoltaic system comprised of photovoltaic cells and the DC/DC boost converter. The mathematical modeling is accomplished in two manners, using the laws of Physics and the Euler-Lagrange approach. In addition, the mathematical modeling also considers the 𝒂𝒃𝒄 and 𝒒𝒅𝟎 reference frames. The mathematical models are validated through simulation in the Matlab/Simulink environment, programming the obtained equations and comparing them with a block model of the simulation environment.

Numerical Study on the Damage Characteristics of Layered Shale Using 3D DEM

Layered shale is a kind of rock with obvious anisotropy, which is significantly influenced by the inclination angle of the rock. In this study, the influence of bedding dip on the strength characteristics, failure mode, and internal fracture evolution of layered shale was investigated through laboratory triaxial compression tests and three-dimensional discrete element numerical simulations. Results show that the numerical model of layered shale constructed using the bonded block model can simulate the layered shale in terms of U-shaped strength variation and failure modes very well. Based on the distribution of cracks and failure characteristics of layered rocks, the failure modes of layered rocks are classified as follows: Shear failure across the bedding plane, slip failure along bedding planes, combined tensile splitting and shear failure. The development of microcracks damage in the slip failure model is controlled by interlayer joints, while in other failure modes, it is jointly controlled by the rock matrix and interlayer joints. The relationship between microscopic joint parameters and the variations of Young's modulus and peak strength has been proposed.

Тестирование и компиляция моделей цифровых блоков в программно-аналитическим комплексе САПР

The article discusses the important stages of the process of developing a digital device of microelectronics associated with testing and compiling models of digital blocks. The work was carried out as part of the creation of a domestic CAD system designed for the design of various digital microelectronics devices. The presented works were carried out by VSFEU together with ROSELECTRONICS Holding. The authors have developed a model of a digital microprocessor based on SYNTACORE's SCR1 core, a 32-bit fully functional RISC-V architecture model with an IMC instruction set. To simulate the RTL model, an XCELIUM simulator with a SimVision visualization shell from Cadence was used, which allows a complete analysis of the RTL model. The core model was compiled using the Genus software from the Cadence development package. Next, the model was configured and optimized according to the time parameters according to the specified restrictions on the microprocessor being developed. It is important to note that effective testing and compilation of digital block models requires the use of specialized tools, such as automated testing tools and version control systems. This makes it possible to significantly speed up the development process and improve the quality of the final product. As a result, a package of files for Innovus software was formed to create a topology.

On the efficacy of higher-order spectral clustering under weighted stochastic block models

Higher-order structures of networks, namely, small subgraphs of networks (also called network motifs), are widely known to be crucial and essential to the organization of networks. Several works have studied the community detection problem–a fundamental problem in network analysis at the level of motifs. In particular, the higher-order spectral clustering has been developed, where the notion of motif adjacency matrix is introduced as the algorithm's input. However, how the higher-order spectral clustering works and when it performs better than its edge-based counterpart remain largely unknown. To elucidate these problems, the higher-order spectral clustering is investigated from a statistical perspective. The clustering performance of the higher-order spectral clustering is theoretically studied under a weighted stochastic block model, and the resulting bounds are compared with the corresponding results of the edge-based spectral clustering. The upper bounds and simulations show that when the network is dense and the edge weights have a weak signal, higher-order spectral clustering can lead to a performance gain in clustering. Real data experiments also corroborate the merits of higher-order spectral clustering.

Nanocrystals Slow-Releasing Ropivacaine and Doxorubicin to Synergistically Suppress Tumor Recurrence and Relieve Postoperative Pain.

Although surgical resection provides a straightforward and effective treatment for most malignant solid tumors, tumor recurrence and acute postoperative pain continue to be two big problems associated with this treatment. To resolve these problems, a nanocrystal composite slow-releasing ropivacaine and doxorubicin was fabricated in this study. Briefly, a self-assembling peptide was used to form nanoparticle complexes with the two drugs, based on which homogeneous nanocrystals were obtained by adjusting the pH. In cultured human melanoma cells, the nanocrystals exhibited improved antitumor activity due to a synergistic effect and enhanced cellular uptake of the two drugs. On the other hand, the nanocrystals could slowly release ropivacaine in vitro and in vivo, generating long-acting analgesia on the rat sciatic nerve block model and incisional pain model. On a nude mouse tumor resection model, the nanocrystals simultaneously suppressed the recurrence of solid tumor and relieved postoperative pain, indicating a potential postoperative treatment for tumor resection patients. This nanocrystal system also suggested a promising and facile strategy for developing multifunctional formulations combining different drugs, which could achieve better therapeutic outcomes in a synergistic and sustained manner.

Indoor millimeter wave D2D communication resource optimization based on improved PMVC and CTRA algorithms

In order to improve the quality of millimeter wave communication in indoor environment and ensure the maximum use of link resources. It is proposed to construct indoor communication transmission characteristics through multi sphere link model and indoor millimeter wave reflection blocking model. At the same time, the improved PMVC algorithm and CTRA algorithm are used to optimize the resource scheduling of links in indoor central scenes and edge scenes respectively. The simulation results show that compared with the original PVC algorithm and greedy algorithm, PMVC has a maximum link throughput of 5.01 Gbps under the optimized scheduling of the improved vertex coloring algorithm, while the maximum throughput of the traditional vertex coloring algorithm and greedy algorithm are 4.73 Gbps and 4.57 Gbps respectively. In the case of fixed link transmission beam width, as the number of link flows increases, the slot throughput of the link decreases continuously. Under the width of 30, the maximum slot throughput of PMVC algorithm is 2.75 Gbps, and the maximum slot throughput of greedy algorithm is 2.48 Gbps; When the beam width is 60, the maximum slot throughput of PMVC algorithm and greedy algorithm is 2.25 Gbps and 1.55 Gbps respectively. The proposed PMVC resource scheduling method can effectively alleviate the shortage of indoor spectrum resources and reduce indoor transmission interference of millimeter wave.

Establishment of A Mouse Model of Stellate Ganglion Block and Subsequent Biphasic Effects on Bilateral Cerebral Cortical Blood Flow

Background and objectives: Stellate ganglion block (SGB) has significant therapeutic efficacy in various clinical practices and further exploration of SGB is needed. The mouse model of SGB had not been reported and the effect on cerebral cortical blood flow (CCBF) was controversial. We aimed to establish an stellate ganglion block (SGB) mouse model and explore how SGB influences CCBF.
 Methods: Male C57BL/6 mice were randomly divided into five groups (n = 6): groups L (left SGB) and R (right SGB) received an injection of 0.25% ropivacaine hydrochloride (0.08 mL) on the respective stellate ganglion; similarly, groups SL (left saline control) and SR (right saline control) received an injection of normal saline (0.08 mL) instead. Group C received no intervention. CCBF was assessed before SGB (T0) and 10 (T1), 30 (T2), 60 (T3), 90 (T4), and 120 min (T5) after SGB using laser speckle contrast imaging system.
 Results: The SGB mouse model was successfully established in groups L and R. Compared with baseline, CCBF on the blocked side decreased at T1, increased at T2–T5, and peaked at T3 in groups L and R (all, P < 0.01). Compared with groups C and SL, the CCBF on the left side decreased at T1 and increased at T2–T5 in group L (all, P < 0.05). A similar trend was noted in groups C and SR relative to group R. The CCBF on the unblocked side decreased at T1, increased at T2–T5, and peaked at T3 in groups L and R (all, P < 0.01).
 Conclusions: The SGB mouse model was established successfully. Unilateral SGB can affect bilateral cerebral cortical blood flow, which shows a transitory decrease followed by a significant increase for at least 2 h.

A theory of pitch for the hydrodynamic properties of molecules, helices, and achiral swimmers at low Reynolds number.

We present a theory for pitch, a matrix property that is linked to the coupling of rotational and translational motion of rigid bodies at low Reynolds numbers. The pitch matrix is a geometric property of objects in contact with a surrounding fluid, and it can be decomposed into three principal axes of pitch and their associated moments of pitch. The moments of pitch predict the translational motion in a direction parallel to each pitch axis when the object is rotated around that axis and can be used to explain translational drift, particularly for rotating helices. We also provide a symmetrized boundary element model for blocks of the resistance tensor, allowing calculation of the pitch matrix for arbitrary rigid bodies. We analyze a range of chiral objects, including chiral molecules and helices. Chiral objects with a Cn symmetry axis with n > 2 show additional symmetries in their pitch matrices. We also show that some achiral objects have non-vanishing pitch matrices, and we use this result to explain recent observations of achiral microswimmers. We also discuss the small but non-zero pitch of Lord Kelvin's isotropic helicoid.

Combinatorial-Probabilistic Trade-Off: P-Values of Community Property Test in the Stochastic Block Models

In this paper, we propose an inferential framework testing the general community combinatorial properties of the stochastic block model. Instead of estimating the community assignments, we aim to test the hypothesis on whether a certain community property is satisfied and provide p-values to assess the statistical uncertainty. For instance, we propose to test whether a given set of nodes belong to the same community or whether different network communities have the same size. We present a general inferential framework that can be applied to all symmetric community properties. To ease the challenges caused by the combinatorial nature of community properties, we develop a novel shadowing bootstrap testing method. By utilizing the symmetry, our method can find a shadowing representative of the true assignment and the number of assignments to be tested in the alternative can be largely reduced. In theory, we introduce a combinatorial distance between two community classes and show a combinatorial-probabilistic trade-off phenomenon in the community property test. Our test is honest as long as the product of the combinatorial distance between two community classes and the probabilistic distance between two assignment probabilities is sufficiently large. On the other hand, we show that such a trade-off also exists in the information-theoretic lower bound of the community property test. We also implement numerical experiments on both the synthetic data and the Protein-Protein Interaction networks to show the validity of our method.

Experimental Study of the influence of PVC casing thickness and well fluid density on prompt fission neutron uranium logging and its corrections

Prompt fission neutron uranium logging is a direct method for measuring uranium content.This method is not influenced by uranium-radium disequilibrium, and provides an accurate and direct way to obtain the uranium content of the formation. However, in field logging, the results of logging are susceptible to the influence of lithology, well fluid and casing. Thus, it must be corrected. Based on the“epithermal /thermal neutron counting rate ratio”(i.e., NE/T ) theory of uranium quantification, a uranium block model is built to simulate field production boreholes. Meanwhile, the influences of PVC casing thickness, well fluid composition and well fluid density on the decay rate of epithermal neutrons and thermal neutrons and the error correction method are investigated. The experimental results show that NE/T increases linearly with increasing thickness of the PVC casing, and the correction equation is μ PVC = -0.0501 dPVC + 1, with a goodness of fit R 2 = 0.9931. The effect of different well fluid compositions and densities on the decay rate of double neutrons is kaolinite ≥ montmorillonite < chlorite < illite. μ_mud follows a quadratic decay law with increasing well fluid density and the fit R 2 < 0.95. Finally, theaverage corrected uranium quantification error is within 5% of the actual uranium content.

Teaching on the Block

This article presents case writing research that explored the pedagogical benefits of teaching in Block mode through a university educators’ perspective. The authors of this research examined their tertiary teaching experiences of Block Model delivery. Through two teacher-authored cases, the researchers engaged in a collaborative practitioner research framework to critically reflect on their own teaching experiences in Block Model to uncover and examine the patterns occurring across iterations of various deliveries. The aim of the research is to examine approaches to teaching and learning in Block and unearth the pedagogical changes required to effectively teach in Block. The aim of this paper is to contribute to our understanding of Block delivery from a teacher perspective and examine the benefits to teaching and learning experienced through Block model delivery. The findings suggest that the systematic foundation of Block delivery, coupled with the immersive nature of Block led to a range of pedagogical benefits such as an enhanced sense of belonging, increased notions of student agency and it promoted scaffolded instruction. The hope is that this classroom-focused research will provide the basis for further research and refinement of Block teaching and learning.

Designing Outdoor Education Units for the Block

In 2018, Victoria University in Melbourne, Victoria, Australia implemented the VU Block Model® for the teaching of undergraduate degree programs. This was a radical shift from a traditional 12-week semester approach and required a complete overhaul of how outdoor education units would be taught moving forward. However, there is a lack of literature on the block mode delivery for outdoor education. The aim of this discussion paper is to identify the challenges of designing and delivering outdoor education in an intensive block mode. To explore this issue, the paper examines unit design and delivery practices undertaken in outdoor education curricula at an Australian university. A reflective practitioner case study research method was applied, with two units being evaluated. This approach was adopted due to the broad range of variables influencing program delivery and student engagement. The discussion is formed around the three years of experience that the authors have in designing, delivering, and reviewing the two units. The outcomes, observations and feedback presented in the discussion suggest that this process has improved the quality of teaching and learning and the student experience. Findings provide practical solutions for delivering and assessing tertiary curriculum outcomes consistent with a nationally recognised framework.

Analyzing the performance improvement of hierarchical binary classifiers using ACO through Monte Carlo simulation and multiclass engine vibration data

Hierarchical binary classifiers are often used for multiclass problems when the number of classes is significantly more. The hierarchical structure suffers from a decrease in detection probability when there is an increase in the number of layers and classes. The order and the choice of classifier used in individual blocks of the hierarchical structure affect the overall probability of detection. In this paper, Ant Colony Optimization (ACO) is proposed to optimize the order of the classifier block at each level. It is also proposed to assign a suitable classifier model for the individual classifier block at each level to maximize the overall probability of detection. The proposed techniques also use an Adaptive boosting (Adaboost) classifier model (weighted average of the constructed classifier) as an alternative approach instead of fixing one classifier model at each classifier block and optimizing the classifier block’s order using ACO. The description using the probability of false negative (miss →pM), and the probability of false positive (false alarm →pF) gives the characteristics of the individual classifier blocks in the hierarchical structure. Monte carlo simulation is performed by randomly assigning values for pM and pF. It was found that the overall detection rate is consistently increasing using the proposed method for various attempts made in the Monte carlo simulation. The performance of the optimized binary hierarchical structures obtained using the proposed technique for the Engine vibration data with 42 classes and 53 block classifiers are compared with the default hierarchical structure. It was observed that there has been a significant improvement in the overall detection rate from 87.235% using the default structure (with Random forest ensemble to classify all classes in the hierarchy) to 90.92% using the proposed technique (ACO with Adaboost). The proposed technique can be used for applications that demand hierarchical, multi-level classifications.

Mapping copper concentrations in tropical open cast mining fronts from X-ray fluorescence and FAAS techniques: A comparative study

Determining copper (Cu) contents and their spatial distribution in tropical open cast mining fronts is crucial for short-term exploitation planning. However, this evaluation in a fast and accurate way can be directly impaired by methods applied. The aim of this work was to assess the analytical performance of portable X-Ray fluorescence (pXRF) for Cu analysis in the mining fronts at the Cu Sossego Mine, in the Carajás Mineral Province, State of Pará, Brazil. For this, 143 drilling samples were collected in mining fronts at the Sequeirinho pit, an area chosen as representative of the heterogeneity of the Cu levels in the deposit of Sossego Mine. The samples were analyzed with three different techniques to determine the Cu levels as follows: pXRF; wavelength-dispersive X-Ray fluorescence (WDXRF); and flame atomic absorption spectrometry (FAAS) after acid digestion with aqua regia (reference method). Results of the three analytical methods were used to generate block models through Leapfroag Geo 6.0 software. Portable XRF data presented a strong positive correlation (>0.70) with the results obtained by the FAAS. In addition, pXRF performed better than WDXRF, with less dispersed values compared to FAAS. Similar distribution maps were generated using the three methods of analysis. After correction, the average Cu content from the pXRF-generated block model was only 0.15% lower than that derived from FAAS data. Therefore, pXRF is a fast, portable, non-destructive, low-cost, accurate and recommendable method for mining front sample analysis and to assist the quality control and geoscience teams in decision-making for feeding the mineral processing plant.

Co-clustering contaminated data: a robust model-based approach

The exploration and analysis of large high-dimensional data sets calls for well-thought techniques to extract the salient information from the data, such as co-clustering. Latent block models cast co-clustering in a probabilistic framework that extends finite mixture models to the two-way setting. Real-world data sets often contain anomalies which could be of interest per se and may make the results provided by standard, non-robust procedures unreliable. Also estimation of latent block models can be heavily affected by contaminated data. We propose an algorithm to compute robust estimates for latent block models. Experiments on both simulated and real data show that our method is able to resist high levels of contamination and can provide additional insight into the data by highlighting possible anomalies.