Location In Space Research Articles

The basis invariant flavor puzzle

The flavor puzzle of the Standard Model quark sector is formulated in a non-perturbative way, using basis invariants that are independent of the choice of quark field basis. To achieve this, we first derive the algebraic ring of 10 CP even (primary) and 1 CP odd (secondary) basis invariants, using the Hilbert series and plethystic logarithm. An orthogonal basis in the ring of basis invariants is explicitly constructed, using hermitian projection operators derived via birdtrack diagrams. The thereby constructed invariants have well defined CP transformation behavior and give the most direct access to the flavor symmetric alignments of basis covariants. We firstly “measure” the orthogonal basis invariants from experimental data and characterize their location in the available parameter space. The experimentally observed orthogonal basis invariants take very close to maximal values and are highly correlated. Explaining the location of the invariants at close to maximal points, including the associated miniscule and highly correlated deviations, corresponds to solving the flavor puzzle in the invariant language. Once properly normalized, the orthogonal basis invariants are close to scale (RGE) invariant, hence, provide exquisite targets for fits of both, low- and high-scale (bottom-up and top-down) flavor models. Our result provides an entirely new angle on the flavor puzzle, and opens up ample opportunities for its ultimate exploration.

Evaluation of the technique of localization of the epidural space with the aid of a peripheral nerve stimulator and epidurographic, comparing two techniques for determining the infused volume, in rabbits (Oryctolagus Cuniculus)

Veterinary care for rabbits has been growing, and, consequently, the anesthetic and analgesic management of this species must be improved. The aim of the present study was to evaluate the technique of localization of the epidural space with the aid of a peripheral nerve stimulator and epidurographic, comparing two techniques for determining the infused volume in rabbits (Oryctolagus Cuniculus). In a prospective, randomized blinded study, six healthy New Zealand rabbits, adults, and weighing from 2.2 kg to 3.8 kg received two treatments, at 1 week intervals: 0.33 mL/kg (treatment I) or 0.05 mL per centimeter of the spine (treatment II) of ioexol epidurally. In both treatments, a peripheral nerve stimulator (2 Hz, 0.25 mA and 0.1 milliseconds) was used to determine the location of the epidural space. Latero-lateral and ventro-dorsal radiographs were taken after five (T5) and twenty-five minutes (T25) of iohexol administration. The epidural space was correctly accessed in 92% of attempts. Treatment I received a smaller volume of contrast than treatment II, 1.0 ± 0.2 mL versus 2.1 ± 0.1 mL (mean ± standard deviation), respectively (p = 0.007). At T5, the cranial progression of the contrast varied between L4 and L5 in treatment I, and L5 and T10 in treatment II. At T25, no contrast was observed in any rabbit. In conclusion, peripheral nerve stimulator aided in accessing the lumbosacral epidural space, and the administration of 0.05 mL per centimeter of the spine resulted in greater cranial progression of contrast.

Analysing access to parks and other green spaces on walking, biking, and driving networks through a socioeconomic lens

ABSTRACT Green spaces are important elements of cities due to their benefits to residents’ physical health, mental health and development, and social connections. Residents are more likely to experience green space benefits when they use them frequently and usage increases when amenities are accessible. Because lower-income households often have less reliable access to automobiles, examining access solely on the road network is inadequate. Do households across the socioeconomic spectrum have access to green space on pedestrian and bicycle networks? After estimating residential locations (origins) from U.S. Census data and park and other green space locations (destinations) from the City of Albuquerque data, we connect the two using service area network analyses in a geographic information system (GIS). Findings suggest that overall green space access is a concern since less than 50% of Albuquerque residents have access to a green space within 400 m, indicating levels below those recommended by the World Health Organization. Park accessibility is relatively equally distributed for low-, middle-, and high-income households across both pedestrian and road networks. Access to other green space is a source of possible inequity with high-income households having more than five times the access to non-park green spaces than low-income households. The bike network presents another source of possible inequity as 39% of high-income households have access to the bike network versus only 30% of low-income households and an expansion of the bike network is a primary recommendation for increasing access in an equitable fashion.

A fluorescence imaging technique suggests that sweat leakage in the epidermis contributes to the pathomechanism of palmoplantar pustulosis

Sweat is an essential protection system for the body, but its failure can result in pathologic conditions, including several skin diseases, such as palmoplantar pustulosis (PPP). As reduced intraepidermal E-cadherin expression in skin lesions was confirmed in PPP skin lesions, a role for interleukin (IL)-1-rich sweat in PPP has been proposed, and IL-1 has been implicated in the altered E-cadherin expression observed in both cultured keratinocytes and mice epidermis. For further investigation, live imaging of sweat perspiration on a mouse toe-pad under two-photon excitation microscopy was performed using a novel fluorescent dye cocktail (which we named JSAC). Finally, intraepidermal vesicle formation which is the main cause of PPP pathogenesis was successfully induced using our "LASER-snipe" technique with JSAC. "LASER-snipe" is a type of laser ablation technique that uses two-photon absorption of fluorescent material to destroy a few acrosyringium cells at a pinpoint location in three-dimensional space of living tissue to cause eccrine sweat leakage. These observatory techniques and this mouse model may be useful not only in live imaging for physiological phenomena in vivo such as PPP pathomechanism investigation, but also for the field of functional physiological morphology.

РАЗРАБОТКА ПРОГРАММНОГО ОБЕСПЕЧЕНИЯ МОДЕЛИРОВАНИЯ ПРОЦЕССОВ ТЕПЛОМАССОПЕРЕНОСА ПРИ МНОГОФАЗНОМ ПОТОКЕ

Mathematical models simulating the process of heat and mass transfer in a multiphase flow and taking into account the thermal conductivity of the working fluid, taking into account its location in space, physical properties and other characteristics, are difficult to implement in the form of software. Usually such models are represented by nonlinear equations, which makes it difficult to implement them correctly using numerical methods. When developing such mathematical models, hydrodynamics, heat transfer of a moving working fluid and the dependence of viscosity on temperature and velocity gradient are not taken into account. (Research purpose) The research purpose is developing a mathematical model of the functioning of the heat supply system as a set of cylindrical pipelines with a heat source through which the working fluid moves. Additional conditions are introduced to achieve high accuracy of calculations at boundary points. The possibility of using analytical equations to calculate the internal heat dissipation during the transportation of the working fluid inside the pipeline is studied. (Materials and methods) Using the two-phase delay theory (DPL-model) and the finite element method (FEM) as flow balancing methods, we obtain a model of the heat exchange of the working fluid motion in the pipeline with the possibility of taking into account relaxation properties. (Results and discussion) The developed algorithm is implemented using the high-level interpreted programming language MATLAB and its simulation environment for complex technical systems Simulink. (Conclusions) Equations modeling the real motion of a multiphase working fluid in locally nonequilibrium systems, including heat supply systems, are obtained. The results obtained make it possible to compile an algorithm and implement it using the high-level interpreted programming language MATLAB, defining a working version of the software for modeling heat and mass transfer processes in a multiphase flow.

Redirected Walking on Omnidirectional Treadmill.

Redirected walking (RDW) and omnidirectional treadmill (ODT) are two effective solutions to the natural locomotion interface in virtual reality. ODT fully compresses the physical space and can be used as the integration carrier of all kinds of devices. However, the user experience varies in different directions of ODT, and the premise of interaction between users and integrated devices is a good match between virtual and real objects. RDW technology uses visual cues to guide the user's location in physical space. Based on this principle, combining RDW technology with ODT to guide the user's walking direction through visual cues can effectively improve user experience on ODT and make full use of various devices integrated on ODT. This paper explores the novel prospects of combining RDW technology with ODT and formally puts forward the concept of O-RDW (ODT-based RDW). Two baseline algorithms, i.e., OS2MD (ODT-based steer to multi-direction), and OS2MT (ODT-based steer to multi-target), are proposed to combine the merits of both RDW and ODT. With the help of the simulation environment, this paper quantitatively analyzes the applicable scenarios of the two algorithms and the influence of several main factors on the performance. Based on the conclusions of the simulation experiments, the two O-RDW algorithms are successfully applied in the practical application case of multi-target haptic feedback. Combined with the user study, the practicability and effectiveness of O-RDW technology in practical use are further verified.

PERFORMANCE ASSESSMENT OF PARABOLIC TROUGH COLLECTORS UNDER CLIMATIC CONDITIONS OF IZMIR, TURKEY: A CASE STUDY

The geographic location of Turkey offers significant potential for renewable energies, especially solar energy. One promising technology for solar energy generation is the parabolic trough collector. To shed light on the advantages of solar energy and the design of solar power plants, this study aims to estimate the heat gain and thermal efficiency of a parabolic trough collector (PTC) under the climatic conditions of Izmir location, which is one of the cities in Turkey that is most exposed to solar energy. In this regard, a comprehensive mathematical model for the PTC systems is developed. The conventional iterative solving approaches are highly sensitive to the initial condition of the process (i.e., if they are initiated from an improper location of the search space they can be easily trapped into local minima). Thus, in this work, to provide a robust framework, the proposed mathematical structure is converted to a constrained optimization model that can be solved using a general optimization technique. Hereof, a gradient-free based method, so-called fuzzy reinforced differential evolution with virtual mutant method is employed. Firstly, to validate the performance of this method, it is tested on existing data given by Sandia National Laboratory. Subsequently, it is employed to resolve the model for the Izmir climatic conditions, which serves as the case study of this work. The performance and heat gain value of parabolic trough collectors under considered climatic conditions are reported and discussed in illustrative tables and diagrams.

Static palpation ain't easy: Evaluating palpation precision using a topographical map of the lumbar spine as a reference.

Clinicians commonly use manual therapy to treat low back pain by palpating the spine to identify the spinous processes. This study aims to evaluate the ability of experienced clinicians to consistently locate the spinous processes from S1 to T12 through palpation. The results will be compared to topographical data representing the lumbar lordosis at baseline and four follow-up time points. In a prior prospective randomized trial, experienced clinicians used palpation to locate the lumbar spinous processes (S1-T12) and then digitized these locations in three-dimensional space. The same digitizing equipment was then used to continuously collect three-dimensional position data of a wheel that rolled along the back's surface through a trajectory that connected the previously digitized locations of the spinous processes. This process was repeated at 4 days, 1, 4, and 12 weeks. The resulting lordosis trajectories were plotted and aligned using the most anterior point in the lordosis to compare the locations of the spinous processes identified in different trials. This way, spinous palpation points could be compared to surface topography over time. Intra- and interrater reliability and agreement were estimated using intraclass correlations of agreement and Bland-Altman limits of agreement. Five clinicians palpated a total of 119 participants. The results showed a large degree of variation in precision estimates, with a mean total value of 13 mm (95%CI = 11;15). This precision error was consistent across all time points. The smallest precision error was found at L5, followed by S1 File, after which the error increased superiorly. Intra- and interrater reliability was poor to moderate. Comparison of palpation results to a topographic standard representing the lumbar lordosis is a new approach for evaluating palpation. Our results confirm the results of prior studies that find palpation of lumbar spinous processes imprecise, even for experienced clinicians.

Spatial Similarity of MRI-Visible Perivascular Spaces in Healthy Young Adult Twins.

This study aimed to determine whether genetic factors affect the location of dilated perivascular spaces (dPVS) by comparing healthy young twins and non-twin (NT) siblings. A total of 700 healthy young adult twins and NT siblings [138 monozygotic (MZ) twin pairs, 79 dizygotic (DZ) twin pairs, and 133 NT sibling pairs] were collected from the Human Connectome Project dataset. dPVS was automatically segmented and normalized to standard space. Then, spatial similarity indices [mean squared error (MSE), structural similarity (SSIM), and dice similarity (DS)] were calculated for dPVS in the basal ganglia (BGdPVS) and white matter (WMdPVS) between paired subjects before and after propensity score matching of dPVS volumes between groups. Within-pair correlations for the regional volumes of dVPS were also assessed using the intraclass correlation coefficient. The spatial similarity of dPVS was significantly higher in MZ twins [higher DS (median, 0.382 and 0.310) and SSIM (0.963 and 0.887) and lower MSE (0.005 and 0.005) for BGdPVS and WMdPVS, respectively] than in DZ twins [DS (0.121 and 0.119), SSIM (0.941 and 0.868), and MSE (0.010 and 0.011)] and NT siblings [DS (0.106 and 0.097), SSIM (0.924 and 0.848), and MSE (0.016 and 0.017)]. No significant difference was found between DZ twins and NT siblings. Similar results were found even after the subjects were matched according to dPVS volume. Regional dPVS volumes were also more correlated within pairs in MZ twins than in DZ twins and NT siblings. Our results suggest that genetic factors affect the location of dPVS.

Analysis of settlement parameters of architecture faculties on university campus

The selection of a suitable place for an activity is an important decision made for a project, which requires assessing it from different points of view. Educational use is one of the most complicated and substantial uses in urban space that requires precise and logical attention to its location and neighborhood with similar and consistent uses. Faculties of universities are educational spaces that should be protected against physical and moral damage to create a healthy educational environment. To do this, it is necessary to find and assess the factors affecting the location of educational spaces. The extant study aimed at finding and assessing the factors affecting the location of educational spaces to locate art and architecture schools or faculties in 4 important universities. The present study is applied developmental research in terms of nature and descriptive-analytical in terms of method. This study used the AHP (Analytical Hierarchy Process) weighing and controlled the prioritization through the TOPSIS (Technique for Order Preference by Similarity) technique in the methodology phase. Since there was no criterion and metric for these centers, six were chosen as the primary metrics after reviewing the relevant theoretical foundations, early investigations, and collecting effective data. Finally, the results indicated the most important factors of vehicular or roadway access, pedestrian access, slope, parking, adjacency, neighborhood, and area. Among the mentioned factors, pedestrian access (w: 0.4231) had the highest weight and was the priority in the location of architecture faculty in studied campuses and areas inside the universities.

Quadratic stability of uncertain large-scale networked systems

In this paper, the quadratic stability of continuous-time uncertain large-scale networked systems is considered. The systems are composed of many subsystems distributed in different locations in space and interconnected according to a certain network topology. A computationally efficient sufficient condition for the quadratic stability of large-scale networked systems is established, utilising effectively the block diagonal structure of the system parameter matrix and the sparseness of the subsystem connection matrix (SCM). Furthermore, a stability condition is presented, which is entirely contingent on the parameters of each subsystem. The simulation results show that the obtained conditions have obvious advantages in analysing the quadratic stability of large-scale networked systems.

KPDet: Keypoint-based 3D object detection with Parametric Radius Learning

3D object detection requires accurate recognition of object category, size, rotation angle, and location in 3D space. Currently, many 3D object detection methods rely on the compact Bird’s Eye View (BEV) or point-wise representations to generate proposals. However, these proposal generation paradigms neglect the spatial distribution of objects, which causes difficulty in estimating the centers of objects. In this paper, we propose a keypoint-based 3D object detector, KPDet, which employs the keypoints in the neighborhood of object centers as the representation for proposal generation. The proposed KPDet first uses voxel-keypoint mapping to aggregate informative features on the subsampled keypoints from voxel-wise features, then calibrates the misalignment between the keypoints and object centers through the Object-aware Feature Pooling (OFP) module. These aligned keypoints with their corresponding features are applied to generate proposals. Since the keypoints are essential components, we further present the Structural Point Abstraction (SPA) module, which captures the anisotropic features of keypoints via constructed structural points to enhance the geometric information. In addition, based on the well-studied multi-task learning framework, we also propose a Parametric Radius Learning (PRL) strategy to adjust the sampling radius of the point-based feature aggregation process during the training procedure. Extensive experiments on the KITI and Waymo Open Dataset show that KPDet could achieve promising results compared with previous works.

Grid-based artificial bee colony algorithm for multi-objective job shop scheduling with manual loading and unloading tasks

This paper investigates a multi-objective job shop scheduling problem with manual loading and unloading tasks (MOJSSPLU) aiming to minimize makespan and total workload simultaneously. Taking human factors into consideration achieves a better balance between production efficiency and resource utilization. To address this problem, we first establish a bi-objective mixed-integer linear programming (MILP) model. Afterward, we combine the artificial bee colony algorithm with the grid technique to develop a grid-based artificial bee colony algorithm (GABC) for solving MOJSSPLU. The algorithm uses a decomposition approach with the earliest-shortest dispatching rule to reduce the complexity of MOJSSPLU. A grid coordinate system is constructed to divide the objective space into cells, facilitating individuals’ location and evaluation in the decision space. Moreover, we focus on improving the cooperation between the employed and onlooker bees and design a mathematical formula based on priority weights to generate onlooker bees to maximize information utilization and improve the exploration and exploitation capabilities of the algorithm. To ensure that the most promising individuals are retained and protected from being eliminated during the evolutionary, we propose an elitist non-dominated solutions reservation strategy for improving the diversity of the population. We further propose a dynamic adjustment of the grid-division method that focuses on improving the exploitation capacity of the algorithm in the objective space to enhance the diversity and convergence of the population. To test the performance of the GABC algorithm, we compare it to the MILP approach and other algorithms using modified benchmark instances. Furthermore, we conduct the Friedman and Wilcoxon nonparametric tests to validate the comparison results among the different algorithms. The computational results demonstrate that the algorithm GABC is efficient.

Проблемы и перспективы современных подходов к изучению стратегий пространственного мышления

Spatial thinking (spatial ability) is an important predictor of success in mathematics, engineering, science and other related fields. Spatial performance is related to a large number of factors, including socio-economic and biological influences. Strategies of spatial thinking, understood as the approach, consciously or unconsciously, chosen to solve a spatial problem, is one of the factors that contribute to overall performance. The literature discusses strategies for solving different spatial tasks, including mental rotation, spatial visualisation, navigation, and mechanical reasoning, which are partly overlapping but also have some distinct features. In this review, we have summarised more than one hundred studies published in leading international journals, identified the main trends, insights and limitations of these studies, and presented possible future directions of this research area. A special emphasis is placed on the contemporary methods for studying spatial strategies, including eye tracking, neuroimaging (EEG, fMRI, fNIRS), non-invasive brain stimulation, and tracking location in space (VR mazes, GPS data). The practical significance of this research is discussed. For example, identifying strategies optimal for performance in a specific task can benefit education, engineering psychology, logistics and usability.

Determinants of subjective outdoor thermal comfort in an urban historic and cultural heritage landscape in Xi’an, China

ABSTRACT In this study, we investigated factors related to subjective outdoor thermal comfort in the Ancient Ming Dynasty Walled City in Xi’an, China. Environmental data were collected from study sites by microclimate monitoring. Survey locations, demographics, psychological characteristics, thermal sensation vote (TSV), and thermal comfort vote (TCV) data were collected from 639 individuals in a questionnaire survey. Generalized linear regression analysis and path analysis were used to understand the associations between the TSV, environmental and psychological factors, and TCV. We found that green space locations, higher age, and greater subjective well-being and environmental satisfaction were associated with increased TCV. The universal thermal climate index was associated with TCV, and this association could have been affected by the individual’s psychological state. Our findings suggest that environmental factors and psychological factors had non-negligible effects on the subjective thermal comfort of individuals located in an open urban area with historical and cultural significance.

Contactless wheat foreign material monitoring and localization with passive RFID tag arrays

In the early stage of harvesting, transportation, and storage, the grain could be mingled with clods from the field, metal pieces from aging machines, and other objects of foreign material, which will greatly influence the grain quality and food security. In this paper, we propose a novel radio frequency (RF) sensing system termed TagSee, which utilizes passive RFID tag arrays to sense the objects buried in wheat. The goal is to simultaneously sense the presence of foreign materials, locate their locations in the 3D space and sense their types, to automatically monitor the stored grain. Specifically, we use RFID received signal strength (RSS) and phase as features for foreign material detection. To design the TagSee system, we first introduce a sensing space division method. Then, an Euclidean Distance Ratio (EDR) algorithm and a heuristic method are proposed to achieve high localization success accuracy. A multi-class SVM method is used to sense different materials properties based on the impact of different foreign materials on signal features. Experimental results show that TagSee can effectively detect foreign materials in stored grain and achieve a centimeter-level localization success accuracy, and can recognize four types of objects in grain.

Usage of Airborne LiDAR Data and High-Resolution Remote Sensing Images in Implementing the Smart City Concept

The cities of the future should not only be smart, but also smart green, for the well-being of their inhabitants, the biodiversity of their ecosystems and for greater resilience to climate change. In a smart green city, the location of urban green spaces should be based on an analysis of the ecosystem services they provide. Therefore, it is necessary to develop appropriate information technology tools that process data from different sources to support the decision-making process by analysing ecosystem services. This article presents the methodology used to develop an urban green space planning tool, including its main challenges and solutions. Based on the integration of data from ALS, CLMS, topographic data, and orthoimagery, an urban green cover model and a 3D tree model were generated to complement a smart-city model with comprehensive statistics. The applied computational algorithms allow for reports on canopy volume, CO2 reduction, air pollutants, the effect of greenery on average temperature, interception, precipitation absorption, and changes in biomass. Furthermore, the tool can be used to analyse potential opportunities to modify the location of urban green spaces and their impact on ecosystem services. It can also assist urban planners in their decision-making process.

Automated analysis of animal behavior and its relation to key aspects of the environment reveals new cognitive specializations of neurons

A thorough analysis of animal behavior is essential for examining the relationship between specific neuron activations with the elements of the external environment, behavior, or internal state. Machine learning techniques have made some advancements in automatic segmentation of animal behavior based on data concerning the location of animal body parts [1–3]. At present, these methods cannot achieve the level of segmentation accuracy desired or make correlations between an animal’s behavioral acts and key environmental factors. To address this issue, the authors have created a software package that can extract a variety of behavioral variables from video recordings of animals in experimental settings, enabling mathematical analysis of a behavioral act continuum. The identification of specific aspects of an animal’s anatomy is crucial for extracting a vast array of behavioral variables. In order to accomplish this task, our team employed DeepLabCut, an accessible toolkit for tracking experimental animal behavior that operates on the principle of transfer learning through deep neural networks. We have devised a technique to ascertain the positions of animal body parts in diverse behavioral situations, resulting in a body parts collection meeting two criteria: offering superior responsiveness to small motor movements of the animal and delivering a high percentage of correct body part locations. In scenarios employing camera shooting from above, such a collection encompasses the nose, ears, tail base, body center, forelimbs, hind limbs, and both flanks of the animal’s body. Next, we created software tools to extract and annotate behavioral variables from data on animal kinematics in various cognitive tasks. Our automated system comprises two main scripting modules: CreatePreset and BehaviorAnalyzer. The CreatePreset module interacts with users to select the type of arena geometry, object location, and necessary temporal and spatial parameters for analysis. The script’s result saves as a mat-file for analyzing the behavior of all experiment videos, assuming a constant relative position of the arena and the video camera alongside the experiment’s design. The BehaviorAnalyzer module conducts initial processing on time series data consisting of coordinates of an animal’s body parts. This results in the formation of a kinematogram, which details the kinematics of the body parts. The module then isolates individual behavioral acts of the animal and annotates its behavior based on motivational and environmental factors. Using mutual information-based methods, we analyzed the specialization of hippocampal CA1 neurons in animals as they explored arenas with varying degrees of novelty. Through the analysis, we have identified neurons that exhibit selectivity in relation to specific continuous kinematic parameters governing the posture and trajectory of the animal. These parameters include the animal’s location in the arena space (X and Y coordinates), as well as the speed and angle of rotation of the animal’s head (i.e. absolute orientation in the arena). Neurons specialized in discrete acts of behavior were identified, including rests, locomotions, freezing, rears, and acts of interaction with objects. Furthermore, a selective activation of neurons was found with regard to an additional set of distinct parameters, which combine the animal’s location in the arena and its speed.

Numerical and Experimental Investigation of a Volumetric Resistance Blower Performance and Its Optimization for Portable Computing Device Applications

Abstract In this paper, we present our results on a relatively new kind of blower called Volumetric Resistance Blower (VRB) for cooling of portable computing platforms like laptop computers. The VRB performance was modeled numerically and compared to traditional bladed blowers. The sources of noise, dominant in bladed blower, are absent in case of VRB, because it uses a continuous porous disk instead of discrete blades. Thus, even though at iso-rpm, VRB yielded lower flowrate, its iso-acoustic performance could be superior. Hence, further analysis was crucial to quantify the potential benefit. The acoustics experiments for bladed blower and VRB were conducted in a hemi-anechoic chamber in accordance with ECMA-74 and ECMA TR/99 standards. Iso-acoustics pressure versus volume flowrate plot for both bladed blower and VRB are compared. VRB was found to have superior performance as compared to bladed blower. The volume flowrate at open flow condition for bladed blower and VRB are comparable, but as back pressure increased the flowrate yielded by VRB kept increasing and at stagnation condition, VRB showed around 79% higher static pressure. In the second part of the work, the experimentally validated numerical model for VRB was used for numerical optimization using a design of experiments (DOE) approach and varying the geometrical parameters. Rotor distance (minimum distance from the axis of rotation of impeller to the cutwater surface) was found to be the most important parameter, and an optimum value was found. A second DOE elucidated the optimal rotor hub center location in the two-dimensional space inside the casing as when the rotor is tucked back into the casing as much as possible and when the rotor distance is above 20.15 mm. A partial P–Q curve is generated (up to 20 Pa) for optimal geometry configuration. Based on the numerical and experimental evidence, VRB is found to have the potential to replace traditional bladed design in portable computing devices. In addition, due to absence of blades, it creates lower tonal noise, giving a much more comfortable experience to the end user.

Spectral clustering and embedding with inter-class topology-preserving

Spectral clustering and embedding are critical in data mining and rely heavily on pre-computed graph structure quality. Some methods simultaneously learn graph structures and low-dimensional embeddings to achieve high-quality graph structures with separable categories. However, existing approaches prioritize inter-class separability while overlooking the inter-class topological structure. Consequently, the learned low-dimensional manifold representations may fail to capture inter-class semantic information, causing the learned graph structures to represent categories partitioning inaccurately. To address these issues, we come up with the inter-class topology and utilize category anchors to indicate class locations in low-dimensional space. The inter-class topology reflects the elaborate structural neighbor information of class, which makes the neighbor classes rationally separable and helps to learn better low-dimensional embedding representations. The spectral embedded clustering method and some variants are proposed to preserve inter-class topology while making categories separable. Furthermore, we ensure intra-class sample compactness in low-dimensional space by assigning sample embeddings near the anchors. We analyze the importance of inter-class topology preserving and intra-class compactness learning. Extensive experiments on publicly available datasets demonstrate that our method is competitive with popular graph clustering and embedding baselines and effectively captures the inter-class topology.