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Leadership research has assumed that leader group prototypicality enhances leadership influence during a leader's tenure. Other leadership research has also assumed that leaders, especially founders, can transform their leadership influence into a legacy that will survive death and departure from the organization and continue to impact followers. However, to understand the historically embedded nature of leadership influence, it is critical to unpack how specific leaders can become group prototypes and influence followers after their departure. We address this opportunity by examining organizational ghosts—former organizational members who become the ideal prototype of an organization's values and identity. Drawing on qualitative data from an organizational merger, our analysis reveals that admired and adored leaders with broad exposure became embodied organizational prototypes. After organizational exit, they became organizational ghosts, institutionalized by associative learning, perpetuated practices, and physical memory work. When activated—either intentionally or organically—these ghosts had "ghostly encounters" (remembered and imagined) with remaining members that safeguarded the organization, comforted organizational members, and devalued alternative value systems. We introduce the concept of organizational ghosts, explain how leaders can become ghosts, and specify remembered and imagined encounters as mechanisms through which former leaders can have enduring influence in organizations. [ABSTRACT FROM AUTHOR]

Line Extensions are among the most common form of product launch in packaged goods markets. As part of this process, brand managers must decide the visual design of the new variant's packaging. To inform this decision making, this research aims to empirically quantify the efficacy of using colors versus images as signals of product variety on pack. We compare the use of color on 576 packs with perceptions of 1,853 category buyers across three categories in the USA. We find that for 84% of variant types, marketers use common colors to signal variety on pack, while consumers perceive that only 56% of variant types are represented by a particular color. Of greater concern, the colors used in practice and those expected by consumers align in only 16% of cases. By comparison, images are linked to variant types to a significantly greater extent (39% of cases). This suggests images are a stronger and more explicit signal of product variety than color. There are multiple implications arising from this study. It expands scholarly research on the use of colors in product extensions and, at the same time, provides a series of valuable benchmarks for industry practice in the portfolio management domain. [ABSTRACT FROM AUTHOR]

Cytoskeletal gels are engineered prototypes that mimic the contractile behavior of a cell in vitro. They are composed of an active polymer matrix and a liquid solvent. Their contraction kinetics is governed by two dynamic phenomena: mechanotransduction (molecular motor activation) and solvent diffusion. In this paper, we solve the transient problem for the simple case of a thin gel slab in uniaxial contraction under two extreme conditions: motor-limited or slow motor (SM) activation regime, and diffusion-limited or fast motor (FM) activation regime. The former occurs when diffusion is much faster than mechanotransduction, while the latter occurs in the opposite case. We observe that in the SM regime, the contraction time scales as t / t 0 ∼ (λ / λ 0) − 3 , with t 0 being the nominal contraction time, and λ and λ 0 being the final and initial stretches of the slab. t 0 is proportional to 1 / w ˙ , where w ˙ is the average mechanical power generated by the molecular motors per unit reference (dry polymer) volume. In the FM regime, the contraction time scales as t / t 1 ∼ (1 − λ / λ 0) 2 , with t 1 being the nominal contraction time, here proportional to the ratio L 2 / D , where L is the reference (dry polymer) thickness, and D is the diffusivity of the solvent in the gel. The transition between the SM and FM regimes is defined by a characteristic power density w ˙ ∗ , where w ˙ ≪ w ˙ ∗ gives the SM regime and w ˙ ≫ w ˙ ∗ gives the FM regime. Intuitively, w ˙ ∗ is proportional to D / L 2 , where, at a given power density w ˙ , a thinner gel slab (smaller L) or including smaller solvent molecules (higher D) is more likely to be in the SM regime given that solvent diffusion will occur faster than motor activation. [ABSTRACT FROM AUTHOR]

Tremendous breakthroughs have been developed in Semi-Supervised Semantic Segmentation (S4) through contrastive learning. However, due to limited annotations, the guidance on unlabeled images is generated by the model itself, which inevitably exists noise and disturbs the unsupervised training process. To address this issue, we propose a robust contrastive-based S4 framework, termed the Probabilistic Representation Contrastive Learning (PRCL) framework to enhance the robustness of the unsupervised training process. We model the pixel-wise representation as Probabilistic Representations (PR) via multivariate Gaussian distribution and tune the contribution of the ambiguous representations to tolerate the risk of inaccurate guidance in contrastive learning. Furthermore, we introduce Global Distribution Prototypes (GDP) by gathering all PRs throughout the whole training process. Since the GDP contains the information of all representations with the same class, it is robust from the instant noise in representations and bears the intra-class variance of representations. In addition, we generate Virtual Negatives (VNs) based on GDP to involve the contrastive learning process. Extensive experiments on two public benchmarks demonstrate the superiority of our PRCL framework. [ABSTRACT FROM AUTHOR]

Research and development of innovative suspension components for rail vehicles have involved huge investments in recent years. Research efforts have focussed on designing and optimising suspension systems to deal with the new challenges introduced in railway dynamics by the continuous increase in vehicle speed. In particular, yaw dampers have been a relevant research topic due to their influence on vehicle stability. In this context, this paper aims to propose a Hardware-In-the-Loop (HIL) methodology for testing yaw dampers under experimental conditions close to real operating scenarios, comparing the influence of different prototypes on the stability of high-speed rail vehicles. A reduced vehicle model is proposed for real-time integration in HIL tests. This model provides a reference stroke to be imposed on the prototype tested, considering the actual damping force provided by the device being analysed. Two yaw damper prototypes are introduced to validate the proposed methodology by means of comparative analysis at different vehicle speeds. The experimental results provided by the HIL test bench are then compared with corresponding analysis done using Multi-Body (MB) simulations. The proposed HIL methodology has proved to be able to test physical prototypes and define guidelines to assist damper manufacturers developing and optimising yaw damper components. [ABSTRACT FROM AUTHOR]

With the effective use of aerators with low energy cost and high aeration performance, aquaculture areas can be developed and supported. The main objective of this study is to determine the optimal physical parameters of high aeration capacity high head conduits and to ensure low energy costs, thus to present a comprehensive review of its usability for pond aeration. In this study, a high-head gated conduit was used as the aeration unit. After obtaining the design that will maximize the aeration performance of the high-head gated conduit, a prototype model was developed to ensure its effective use in pond aeration. The parameters affecting the performance of this developed aeration system and the corresponding energy cost values were determined. According to the results, the most important parameters affecting the aeration performance are, respectively, flow rate, the opening of the gate, hydrostatic level, and jet plunge angle. In the optimal design, more than three times the unit volume of water circulating in the system is added to the system. The cost value of this operation in terms of energy was measured as 0.10 kWh/m3 air. The developed system was found to have significantly higher energy efficiency values compared to alternatives, based on specific energy consumption data. [ABSTRACT FROM AUTHOR]

On-chip networks (NoCs) have become a popular choice for designing large multiprocessor architectures. Software-based emulation is often used to perform the design verification. However, if the considered design is sufficiently large, software-based emulation becomes impractically slow. To avoid this limitation, multi-FPGA emulation was introduced, where multiple interconnected FPGAs collectively emulate a single circuit. The number of external FPGA pins is often insufficient for emulating large network-on-chip designs accurately. As a result, the overall emulation frequency has to be severely limited. We propose a method for accelerating multi-FPGA emulation by reducing the amount of data FPGAs need to transmit to each other. To achieve cycle-accurate emulation in the absence of constant transmission latency, synchronous messaging is implemented. The proposed method was tested on a functioning prototype. It is shown that the use of our method for multi-FPGA emulation of large NoC designs can reach several orders. [ABSTRACT FROM AUTHOR]

Few-shot remote sensing scene classification identifies new classes from limited labeled samples where the great challenges are intraclass diversity, interclass similarity, and limited supervision. To alleviate these problems, a teacher-student prototype enhancement network is proposed for a few-shot remote sensing scene classification. Instead of introducing an attentional mechanism in mainstream studies, a prototype enhancement module is recommended to adaptively select high-confidence query samples, which can enhance the support prototype representations to emphasize intraclass and interclass relationships. The construction of a few-shot teacher model generates more discriminative predictive representations with inputs from many labeled samples, thus providing a strong supervisory signal to the student model and encouraging the network to achieve accurate classification with a limited number of labeled samples. Extensive experiments of four public datasets, including NWPU-remote sensing image scene classification (NWPU-RESISC45), aerial image dataset (AID), UC Merced, and WHU-RS19, demonstrate that this method achieves superior competitive performance than the state-of-the-art methods on five-way, one-shot, and five-shot classifications. [ABSTRACT FROM AUTHOR]

RelationNet is a highly effective metric-based few-shot learning method. However, RelationNet uses only shallow convolutional networks in the feature extraction stage, yielding less representative sample features. In addition, RelationNet simply uses summing or averaging to compute prototypes in the prototype learning stage, making it difficult to obtain very representative prototypes. To address these two aspects, we propose a Relation Network with Dual-Channel Feature Fusion for Few-shot Learning(ReNDCF). Firstly, in the feature extraction stage, a Dual-Channel feature extractor is proposed and a multi-head self-attention mechanism is introduced to enhance the feature extraction ability for fine-grained samples by exploiting the correlation between sample categories. Secondly, in the prototype learning module, an improved adaptive prototype learner is proposed, which further enables the final prototype to represent a certain class of samples more accurately. Finally, our ReNDCF achieves better classification performance than RelationNet and other state-of-the-art classification methods on three widely used fine-grained benchmark datasets CUB-200-2011, Stanford-Cars, and Stanford-Dogs. [ABSTRACT FROM AUTHOR]

Few-shot learning is used in the development of models that can acquire novel class concepts from limited training samples, facilitating rapid adaptation to novel, intricate, and varied tasks encountered in real-world scenarios. Compared to meta-training, traditional batch training exhibits superior efficiency. However, when addressing few-shot learning tasks, the features extracted by batch-trained models often struggle to effectively represent novel class concepts, resulting in unsatisfactory performance. This challenge arises from two primary issues. First, the models lack the capacity to autonomously map novel class features into an effective discriminant subspace, resulting in the interference of class-independent feature components during metric calculations. Second, the limited sample size hinders the ability of the model to accumulate valuable experience, leading to representations that deviate from the true class center. To address these issues, we introduce the Class Feature Sub-space (CFS-space) as an effective discriminant space for few-shot classification; it preserves class features and suppresses noise components by mapping the extracted features into the CFS-space. Furthermore, we incorporate empirical knowledge from the base set and calibrate the prototypes within the CFS-Space to enhance the class representations. Ablation studies affirm the efficacy of our approach. As evaluated in 5-way 1/5-shot tasks, our method achieves impressive accuracies of 66.42%/83.69% on mini-ImageNet, 72.07%/86.36% on tiered-ImageNet, and 79.34%/90.42% on CUB, significantly narrowing the performance gap between the batch-training and the meta-training paradigm. [ABSTRACT FROM AUTHOR]

Few-shot segmentation (FSS) aims to segment novel classes given a small number of labeled samples. Most of the existing studies do not fine-tune the model during meta-testing, thus biasing the model towards the base classes and preventing the prediction of novel classes. Other studies only use support images for fine-tuning, which biases the model towards the support images rather than the target query images, especially when there is a large difference between the support and the query images. To alleviate these issues, we propose an e ̲ fficient f ̲ ine- t ̲ uning network (EFTNet) that uses unlabeled query images and predicted pseudo labels to fine-tune the trained model parameters during meta-testing, which can bias the model towards the target query images. In addition, we design a query-to-support module, a support-to-query module, and a discrimination module to evaluate which fine-tuning round the model achieves optimal results. Moreover, the query-to-support module also takes the query images and their pseudo masks as part of the support images and support masks, which causes the prototypes to contain query information and tend to obtain better predictions. As a new meta-testing scheme, our EFTNet can be easily combined with existing studies and greatly improve their model performance without repeating the meta-training phase. Many experiments on PASCAL- 5 i and COCO- 20 i prove the effectiveness of our EFTNet. The EFTNet also achieves new state-of-the-art performance. Codes are available at https://github.com/Jiaguang-NEU/EFTNet. [ABSTRACT FROM AUTHOR]

Few-shot Semantic Segmentation (FSS) was proposed to segment unseen classes in a query image, referring to only a few annotated examples named support images. One of the characteristics of FSS is spatial inconsistency between query and support targets, e.g., texture or appearance. This greatly challenges the generalization ability of methods for FSS, which requires to effectively exploit the dependency of the query image and the support examples. Most existing methods abstracted support features into prototype vectors and implemented the interaction with query features using cosine similarity or feature concatenation. However, this simple interaction may not capture spatial details in query features. To address this limitation, some methods utilized pixel-level support information by computing pixel-level correlations between paired query and support features implemented with the attention mechanism of Transformer. Nevertheless, these approaches suffer from heavy computation due to dot-product attention between all pixels of support and query features. In this paper, we propose a novel framework, termed ProtoFormer, built upon the Transformer architecture, to fully capture spatial details in query features. ProtoFormer treats the abstracted prototype of the target class in support features as the Query and the query features as Key and Value embeddings, which are input to the Transformer decoder. This approach enables better capture of spatial details and focuses on the semantic features of the target class in the query image. The output of the Transformer-based module can be interpreted as semantic-aware dynamic kernels that filter the segmentation mask from the enriched query features. Extensive experiments conducted on PASCAL- 5 i and COCO- 20 i datasets demonstrate that ProtoFormer significantly outperforms the state-of-the-art methods in FSS. [ABSTRACT FROM AUTHOR]

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Low-frequency vibration isolation is essential for ultra-precision manufacturing and measurement equipment. Low stiffness is beneficial for low-frequency isolation, while leading to a degradation of the load capacity of the isolator. To tackle the problem, a nonlinear isolator is proposed with a cross-ring structure, composed of a circular ring and a semi-circular ring. Experimental studies validate that the isolator is applicable to different payload mass, and a cut-off frequency of 1.1 Hz is achieved for an effective isolation. The isolator is theoretically investigated to reveal the mechanism leading to the low-frequency isolation performance. An elliptic integral method is adopted to characterize the stiffness characteristics of the ring structures under compression. The whole compression process of a semi-circular ring is divided into five stages according to the deformed shapes, exhibiting quasi-linear stiffness, stiffness-softening, negative stiffness, and stiffness-hardening characteristics in sequence. Together with the stiffness-softening circular ring, the cross-ring structure demonstrates a growing high-static-low-dynamic-stiffness (HSLDS) characteristic in a wide load range, and the result is verified by a restoring force measurement test. A harmonic balance analysis is performed to predict the frequency responses of the proposed isolator. It is shown that a low-frequency isolation can be achieved with the structure compressed to the HSLDS region by the payload, and an ultra-low-frequency isolation is achieved with the dynamic-to-static stiffness ratio below 0.1. A numerical investigation is performed to further reveal the frequency responses of the isolator with lightweight/overweight payloads and excessive excitation amplitudes. Jump phenomena are presented. This work provides a prototype and the theoretical basis for low-frequency vibration isolation via a cross-ring structure. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Hemocompatibility remains the dominant challenge in rotary blood pumps, and more information on the relationship between individual pump design features, hemodynamics, and blood trauma in various operation conditions is necessary. The study evaluated the variation of gap sizes in extracorporeal blood pumps concerning their influence on blood compatibility, particularly during off‐design conditions.We developed a parametric generic blood pump framework for in‐silico and in‐vitro design feature analysis. Thirty‐six designs with varying axial and radial gap sizes between 0.5 mm and 3 mm were generated. CFD was applied to calculate and compare device hemodynamics and evaluate the performance and hemocompatibility during off‐design and target operation conditions. The following quantities were analyzed: pressure difference, hemolysis potential, residence times, hydraulic efficiency, and recirculation ratio.The in‐vitro prototype showed excellent agreement with in‐silico predictions regarding hydraulic performance (R2 = 0.996 with a RMSE = 2.07). Our results show a modest impact of gap size variations ±10% on key metrics. Domain‐resolved analyses revealed a significant contribution of the gap regions to the device's overall hemolytic performance, with an increasing contribution for off‐design flow rates. Overall elevated hemolysis levels were identified if at least one gap size was held minimal.We introduced and showed the feasibility of a parametric rotary blood pump framework to systematically investigate design feature impact. Results suggest, larger and uniformly sized gaps being overall beneficial regarding hemocompatibility. [ABSTRACT FROM AUTHOR]

ABSTRACT In this article, a bidirectional DC‐AC modulation strategy for series resonant dual active bridge converter (SR‐DAB) is proposed. This modulation strategy combines phase shift (PS) and variable frequency (VF), which utilize four control variables, namely, three PS ratios and switching frequency. Three of four control variables are used for every operating scenario. Modulation methods under both buck and boost modes are considered and designed to attain a wide voltage gain range. Situations when modulation variables reach near transition limits are also given attention by introducing the notion of transition mode to realize smooth transition. The modulation strategy is optimized and designed by considering the operating constraints and the power losses in all aspects. Comparison of this optimization strategy with other strategies is carried out to prove the advantages of the proposed strategy. Finally, a 500‐W prototype is designed and built, which can operate under the condition of input DC voltage 10–50 V and output AC voltage 220 Vrms, 50 Hz, and the measured peak efficiency reaches 96.2%. [ABSTRACT FROM AUTHOR]

Drawing on previous work, I argue that a family resemblance account of the concept woman has several beneficial consequences. Namely, it promotes hermeneutical justice, and, in time, it may serve to change the prototypes and stereotypes people tend unreflectively to associate with woman. I claim that only at that point will full hermeneutical justice be achieved. To this end, I propose a reconceptualization of the notion of hermeneutical injustice, first presented by Fricker (2007). First, I present the family resemblance account of woman. Accordingly, that concept isn’t identified by a set of necessary and (jointly) sufficient conditions, but, roughly, by different criteria. Second, I show how concepts, prototypes and stereotypes relate to one another and how they may contribute to hermeneutical injustice. Finally, I show how the proposed account of woman may in time foster a change in the associated prototype and stereotypes, which will ameliorate societies by doing more justice to the lived experience of trans women – that is, by promoting full hermeneutical justice. [ABSTRACT FROM AUTHOR]

Few-shot hyperspectral image classification aims to develop the ability of classifying image pixels by using relatively few labeled pixels per class. However, due to the inaccuracy of the localization system and the bias of the ground survey, the potential noisy labels in the training data pose a very significant challenge to few-shot hyperspectral image classification. To solve this problem, this paper proposes a weighted contrastive prototype network (WCPN) for few-shot hyperspectral image classification with noisy labels. WCPN first utilizes a similarity metric to generate the weights of the samples from the same classes, and applies them to calibrate the class prototypes of support and query sets. Then the weighted prototype network will minimize the distance between features and prototypes to train the network. WCPN also incorporates a weighted contrastive regularization function that uses the sample weights as gates to filter the fake positive samples whose labels are incorrect to further improve the discriminative power of the prototypes. We conduct experiments on multiple hyperspectral image datasets with artificially generated noisy labels, and the results show that the WCPN has excellent performance that can sufficiently mitigate the impact of noisy labels. [ABSTRACT FROM AUTHOR]

This paper proposes an effective method to improve the power efficiency of the flyback converter in the continuous conduction mode (CCM). The proposed converter uses a simple passive circuit to reduce the switching power losses. The current through the output diode can be shifted to a new branch where one diode, one inductor, and one auxiliary winding of the transformer are included. The output diode current can be reduced to zero for the zero-current switching of the output diode. The additional inductor is used to control the changing rate of the additional diode current to reduce the reverse-recovery current. Keeping the simplicity of the passive method, the proposed converter improves the power efficiency compared to the conventional converter. The circuit configuration and the operation principle are described. The design considerations are presented, including the simulation verification. The experimental results for a 45 W prototype are discussed to evaluate the performance of the proposed converter. The proposed converter has achieved a power efficiency of 93.5% for the rated load condition, improving the power efficiency. The applications of the proposed converter are also discussed for the future research directions. [ABSTRACT FROM AUTHOR]

The self-rectifying memristor (SRM) is a promising device prototype for high-density three-dimensional (3D) integration and high-efficiency in-memory computing (IMC) by virtue of its ability to effectively suppress sneak current, simple device structure, and low energy consumption. Theoretically understanding the intrinsic mechanisms of SRM is a matter of concern. Here, we fabricated a Ta/TaOx/HfO2/Pt-stacked SRM exhibiting >103 on/off ratio, rectification ratio, and nonlinearity. The SRM can be repeatedly programmed by more than 106 pulses and demonstrates robust retention and high scalability (∼59 Mbit). A reasonable interface model for this SRM is established based on first-principles calculations. Using self-energy corrected density function theory, we calculate the barrier heights at each interface. Detailed I–V curve fitting and energy band analysis are performed and computationally verified to explain the intrinsic reasons for resistive switching, self-rectifying, and nonlinear behaviors. The work may advance the development of SRM prototype to enable energy-efficient 3D IMC. [ABSTRACT FROM AUTHOR]

This paper presents a simple switched‐coupled‐inductor inverter (SCII), as well as completes the relevant analysis, design, and implementation, for efforts aimed at achieving boost DC‐AC inversion and strengthening closed‐loop regulation. In structure, the power‐part circuit consists of switched‐coupled‐inductor booster and half‐bridge DC‐link inverter, connected in cascade between supply VS$$ {V}_S $$ and output Vo$$ {V}_o $$ to work for the AC output range as 1+nD/1−DVS~−nVS$$ \left[\left(1+ nD\right)/\left(1-D\right)\right]{V}_S\sim -n{V}_S $$ (n: turn ratio, D$$ D $$: ratio cycle). As adopting VS=24V$$ {V}_S=24\ \mathrm{V} $$, D=0.42$$ D=0.42 $$, n=6$$ n=6 $$, the output Vo$$ {V}_o $$ can be lifted to +144V~−144V$$ +144\ \mathrm{V}\sim -144\ \mathrm{V} $$ (i.e., DC 24 V to AC 100 Vrms, 60 Hz). In control, the control‐part circuit consists of phase generator and sinusoidal pulse‐width‐modulation (SPWM) block and generates driver signals of switches according to the feedback signal of Vo$$ {V}_o $$ for the needs of timing sequence (to different topologies) and output regulation/robustness (to various desired output/loading variation). The related chip circuit is designed via pre‐/post‐layout Cadence procedure and then practically is implemented on a real chip (D35‐106B‐E0027, TSMC 0.35 μm, 1500 × 1500 μm2, 3.3 V, 2.146 mW, 100 kHz max., 18S/B) via the assistance of TSMC and Chip Implementation Center (CIC). In theory, some relevant analysis and design will be discussed, such as modeling, conversion ratio, power efficiency, parameter selection, system stability, and control design. In implementation, several simulation/experiment cases via testing on the SCII's prototype circuit are illustrated to examine the efficacy of the proposed scheme. [ABSTRACT FROM AUTHOR]

Pressure suppression containment has been adopted extensively in boiling water reactor design due to its remarkable pressure suppression capacity. To study the pressure response characteristics of the containment in the initial stage of the loss-of-coolant accident, it is necessary to build a scaling facility to simulate the prototype. Analysis of the steam mass and energy that are released from the break as well as of the steam condensation that occurs in the suppression pool is conducted, respectively, for the prototype pressurized water reactor. The suppression pipe system resistance is also scaled with a certain ratio. The length and diameter of the main pipe and the branch pipe as well as the orifice diameter are calculated. At last, the prototype and the experimental facility are modeled by MELCOR to analyze the steam mass and energy release. The results show that the containment pressure evolution trends of the prototype and the scaled experimental facility are consistent. The pressure difference exists at some times, with a maximum relative error of 4%. [ABSTRACT FROM AUTHOR]

In order to solve the contradiction between the rapid isolation of low voltage DC faults and the low bounce of small stroke vacuum switches, taking the fast vacuum switch for 400 V DC power distribution system as the research object, the electromagnetic buffer simulation and experimental research in the opening process are carried out. The influencing factors of the dynamic and reaction mechanism and buffer output characteristics are analyzed, and the electromagnetic buffering effect under typical working conditions is simulated, which proves that electromagnetic buffer is a necessary part of 400 V fast vacuum switch and the motion characteristics of fast switching are optimal when applying 220 V electromagnetic buffer. According to the simulation calculation results, the engineering prototype was made, the experimental research on the electromagnetic buffer under typical working conditions was carried out, and the design criteria of the small stroke electromagnetic buffer were proposed, which solved the problem of fast switching of small stroke and reliable control and low bounce. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This study developed and evaluated a prototype for augmented reality (AR) interaction among multiple users sharing a three-dimensional hologram within a shared physical space. A systems requirements analysis was conducted to determine necessary interactions, followed by an iterative implementation plan with testing at each step. The application for the HoloLens 2 (HL2) headset was developed using Unity for 3D design, C# for programming, and Photon for multiplayer capabilities. The prototype was evaluated in a user study utilizing custom and NASA TLX questionnaires, comparing participants' self-reported task success with recorded data to assess the accuracy of selfassessments. The prototype effectively facilitated multi-user interactions within a shared environment, achieving acceptable synchronization for two users. Most participants successfully completed tasks, with TLX scores indicating low cognitive and mechanical load during AR task execution. This study demonstrates AR's viability for displaying and manipulating complex three-dimensional structures within a collaborative medical context among multiple individuals in the same physical space. [ABSTRACT FROM AUTHOR]

The probe and singular sources methods are two well-known classical direct reconstruction methods in inverse obstacle problems governed by partial differential equations. In this paper, by considering an inverse obstacle problem governed by the Laplace equation in a bounded domain as a prototype case, an integrated theory of the probe and singular sources methods is proposed. The theory consists of three parts: (i) introducing the singular sources method combined with the notion of the probe method; (ii) finding a third indicator function whose two ways decomposition yields the indicator functions in the probe and singular sources methods; (iii) finding the completely integrated version of the probe and singular sources methods. [ABSTRACT FROM AUTHOR]

This paper describes a measuring unit for synchronously collecting the air dose rate and measurement position for efficient dosimetry surveying and data logging. The developed prototype comprises a three-dimensional light detection and ranging-based mapping part and dosimetry part, which are integrated into a single measuring unit through an embedded computer that installs a ROS (robot operating system) framework. The unit can function as a standalone system with embedded batteries. Since it is portable, on-line data gathering in the workspace can be realized, thereby maintaining consistency between the air dose rate and measurement position. In this paper, we describe the functional requirements for the measuring unit, the prototype system configuration, and the experimental results obtained in the mockup environment and nuclear facility to discuss its performance. [ABSTRACT FROM AUTHOR]

In order to improve the vibration isolation performance of current three-parameter damper using bellow and fluid damping, a concept of fluid damper with variable damping and secondary variable stiffness was proposed, a prototype has been designed with several frequency selective valves to adjust the damping characteristics at specific frequency bands, especially that in the low-frequency range. Followed mathematical modelling and simulation of the damper have been carried out, the results show that the designed damper has obtained excellent damping characteristics both in the high- and low-frequency ranges, the micro-vibration isolation efficiency of the damper under realistic excitation of a Control Moment Gyroscope used in a manned spacecraft reaches a significant 71.03 %.The proposed damper concept and designed prototype have laid the foundation for further testing and optimization of high-end isolators for modern spacecrafts. [ABSTRACT FROM AUTHOR]

Automated sorting of sweetpotatoes is necessary to reduce labor dependence and costs that are significant at today's sweetpotato packing sheds. Although optical sorters have been widely adopted in commercial packing lines for many horticultural commodities, there remains an unmet need to develop dedicated technology for the automated grading and sorting of sweetpotatoes. Sorting mechanisms are the critical component that physically segregates products according to quality grades determined by a machine vision or imaging system. This study presents the new engineering prototypes and evaluation of three different pneumatically powered mechanisms for sorting sweetpotatoes online. Among the three sorters, the sorting mechanism, which employs a linear air cylinder to drive a paddle directly striking products, achieved the best overall accuracy and repeatability of 98% and 96.8%, respectively, at conveyor speeds of 4–12 cm/s. The sorter based on a rotary actuator also delivered decent accuracy and repeatability of 97.9% and 95.6%, respectively. The best-performing sorting mechanism was integrated with a machine vision system that graded sweetpotatoes based on size and surface defect conditions to separate graded sweetpotatoes into three quality categories. The errors of 0–1% due to the sorting process were obtained at conveyor speeds of 4–12 cm/s, confirming the efficacy of the manufactured sorting mechanisms. There was a declining trend with the conveyor speed in the performance of the sorting mechanisms when evaluated either in a standalone or integrated configuration. The proposed sorting mechanisms that are simple in construction and operation and of low cost are useful for developing a more full-fledged sorting system. More research is needed to enhance sorting performance and conduct extensive tests at higher conveyor speeds for practical application. [ABSTRACT FROM AUTHOR]

This paper highlights the importance of one-shot learning from prototype Stock Keeping Unit (SKU) images for efficient product recognition in retail and inventory management. Traditional methods require large supervised datasets to train deep neural networks, which can be costly and impractical. One-shot learning techniques mitigate this issue by enabling classification from a single prototype image per product class, thus reducing data annotation efforts. We introduce the Variational Prototyping Encoder (VPE), a novel deep neural network for one-shot classification. Utilizing a support set of prototype SKU images, VPE learns to classify query images by capturing image similarity and prototypical concepts. Unlike metric learning-based approaches, VPE pre-learns image translation from real-world object images to prototype images as a meta-task, facilitating efficient one-shot classification with minimal supervision. Our research demonstrates that VPE effectively reduces the need for extensive datasets by utilizing a single image per class while accurately classifying query images into their respective categories, thus providing a practical solution for product classification tasks. [ABSTRACT FROM AUTHOR]

The prototype analysed is based on the structure of a gantry made to scale for didactic purposes, relating its dimensions to large structures used in buildings. The present work contributes substantially in the vibrational analysis of structures, simulating in a practical way the behaviour of the portal against the action of external loads. Additionally, the contribution provided by the incorporation of a viscous damper in the structure is observed. The structure includes a mechanism that generates dynamic loads inducing horizontal movement in the system exactly as it happens during a telluric movement. The graphs that characterize the movement of the system are obtained, showing the notable reduction of the acceleration when including a viscous shock absorber. The behavior of a building that incorporates a viscous dampening system in its gantry presents ideal characteristics during a seismic movement reducing the damage generated to the structure during the event. [ABSTRACT FROM AUTHOR]

In this paper, a novel wideband circularly polarized (CP) array antenna is proposed. The array element is composed of four driven patches, four parasitic patches, and a loop feeding structure. On the basis of the array element structure, 1 × 2 and 2 × 2 arrays with shared patches are formed separately. Compared with the traditional structure, the volume of the 1 × 2 array antenna which only shares the patches in the x direction is reduced by 15%, and the volume of the 2 × 2 array antenna which shares the patches in the x and y directions is further reduced by 28%. The cleverness of this method is that it can keep the impedance bandwidth almost unchanged. To validate the simulated results, antenna prototypes are fabricated and measured. The results of the measurements demonstrate that the impedance bandwidths of the 1 × 2 and 2 × 2 array antennas are 27.2% (5.40–7.10 GHz) and 35.7% (5.22–7.49 GHz), respectively, and the 3 dB axial ratio (AR) bandwidths are 22.7% (5.31–6.67 GHz) and 25.4% (5.47–7.06 GHz), respectively. In addition, the measured data show that the 1 × 2 array exhibits a peak gain of 11.1 dBic, and the 2 × 2 array achieves a peak gain of 12.6 dBic. Both of them achieve a flat gain with a maximum ripple of less than 1.3 dB over the whole operating band. [ABSTRACT FROM AUTHOR]

This study evaluates the prediction of MJO teleconnections in two versions of the NOAA Unified Forecast System (UFS): prototype 5 (UFS5) and prototype 6 (UFS6). The differences between the two prototypes in the number of vertical layers (64 in UFS5 vs. 127 in UFS6) and the model top (54 km in UFS5 vs. 80 km in UFS6) can potentially impact the prediction of MJO teleconnections. With respect to ERA-Interim, the global teleconnections of the MJO to the Northern Hemisphere show similar biases in 500 hPa geopotential height over the North Atlantic and European sectors in both prototypes, whereas UFS6 has slightly smaller biases over the North Pacific region. Both prototypes capture the extratropical cyclone activity occurring in weeks 3–4 over the North Atlantic after the MJO phases 6–7 and over the North Pacific and North America after MJO phases 4–5. Both prototypes successfully forecast the sign and approximate locations of 2-m temperature anomalies over the mid-to-high latitude continents occurring in weeks 3–4 after MJO phase 3 but fail to capture the sign reversal of anomalies over North America between weeks 3 and 4 after MJO phase 7. Overall, the two prototypes show similar performance in simulating the tropospheric basic state as well as prediction skill of the MJO and MJO teleconnections, suggesting that the increase in model vertical resolution and model top does not strongly improve the prediction of MJO teleconnections in the troposphere in UFS. [ABSTRACT FROM AUTHOR]

Structural systems based on tension and compression play a significant role in maximizing the performance of materials. Among them, structures based on the concept of tensegrity have attracted attention owing to their elegant design features and floating feeling. However, the complex construction of tensegrity-based structures hinders their implementation in practical design and architectural applications. Herein, we propose a novel tensegrity-based unit with simple connectivity and manufacturability. The external form of this unit is similar to that of a space-filling polyhedron. The prototype of the proposed unit is constructed, and the simple tension management of the unit is demonstrated. The mechanical behavior of the assembled structure is investigated by performing loading tests and numerical analyses. The behavior can be accurately predicted and general design can be applied to develop structures for practical applications. [ABSTRACT FROM AUTHOR]

Traditional machine learning-based entity extraction methods rely heavily on feature engineering by experts, and the generalization ability of the model is poor. Prototype networks, on the other hand, can effectively use a small amount of labeled data to train models while using category prototypes to enhance the generalization ability of the models. Therefore, this paper proposes a prototype network-based named entity recognition (NER) method, namely the FSPN-NER model, to solve the problem of difficult recognition of sensitive data in data-sparse text. The model utilizes the positional coding model (PCM) to pre-train the data and perform feature extraction, then computes the prototype vectors to achieve entity matching, and finally introduces a boundary detection module to enhance the performance of the prototype network in the named entity recognition task. The model in this paper is compared with LSTM, BiLSTM, CRF, Transformer and their combination models, and the experimental results on the test dataset show that the model outperforms the comparative models with an accuracy of 84.8%, a recall of 85.8% and an F1 value of 0.853. [ABSTRACT FROM AUTHOR]

A photovoltaic (PV) power forecasting prediction is a crucial stage to utilize the stability, quality, and management of a hybrid power grid due to its dependency on weather conditions. In this paper, a short-term PV forecasting prediction model based on actual operational data collected from the PV experimental prototype installed at the engineering college of Misan University in Iraq is designed using various machine learning techniques. The collected data are initially classified into three diverse groups of atmosphere conditions—sunny, cloudy, and rainy meteorological cases—for various seasons. The data are taken for 3 min intervals to monitor the swift variations in PV power generation caused by atmospheric changes such as cloud movement or sudden changes in sunlight intensity. Then, an artificial neural network (ANN) technique is used based on the gray wolf optimization (GWO) and genetic algorithm (GA) as learning methods to enhance the prediction of PV energy by optimizing the number of hidden layers and neurons of the ANN model. The Python approach is used to design the forecasting prediction models based on four fitness functions: R2, MAE, RMSE, and MSE. The results suggest that the ANN model based on the GA algorithm accommodates the most accurate PV generation pattern in three different climatic condition tests, outperforming the conventional ANN and GWO-ANN forecasting models, as evidenced by the highest Pearson correlation coefficient values of 0.9574, 0.9347, and 0.8965 under sunny, cloudy, and rainy conditions, respectively. [ABSTRACT FROM AUTHOR]

Multi-functional photovoltaic (PV) inverters incorporate ancillary services to enhance power quality and mitigate stability issues in distribution networks. These next-generation PV inverters will achieve a higher utilization of the inverter's rated capacity, improving the cost-effectiveness of PV technology. However, the power required to perform ancillary services, such as load compensation capabilities, could exceed the inverter's capacity, risking the components' integrity. Therefore, multi-functional control algorithms must limit the power capacity according to the system's nominal currents. Despite this, most control proposals do not address this issue when load balancing capabilities are included for PV inverter control. This paper proposes a flexible control strategy for three-phase multi-functional PV inverters, considering load balancing functionalities while keeping the inverter currents within safe operating limits. The proposal introduces two control parameters whose variation results in different load compensation capabilities. These parameters can be adapted dynamically according to the inverter rated capacity not used for active power injection and the load compensation requirements. Additionally, a control algorithm is proposed to limit the inverter current according to the nominal values supported by the device. This algorithm also allows setting compensation objectives following a priority scheme in which the injection of the PV active power is prioritized over the load compensation functionalities. Reactive power compensation and load balancing functionalities are also considered at a lower level of hierarchical priority. The proposal was evaluated through experimental tests on a multi-functional PV inverter prototype under various operational conditions. The experimental results show an excellent control strategy performance, achieving the control objectives under unbalanced load conditions. [ABSTRACT FROM AUTHOR]

TEMPUS is a new detector system being developed for photon science. It is based on the Timepix4 chip and, thus, it can be operated in two distinct modes: a photon‐counting mode, which allows for conventional full‐frame readout at rates up to 40 kfps; and an event‐driven time‐stamping mode, which allows excellent time resolution in the nanosecond regime in measurements with moderate X‐ray flux. In this paper, the initial prototype, a single‐chip device, is introduced, and the readout system described. Moreover, and in order to evaluate its capabilities, some tests were performed at PETRA III and ESRF for which results are also presented. [ABSTRACT FROM AUTHOR]

Edge analytics receives an ever-increasing interest since processing streaming data closer to where they are produced, rather than transferring them to the cloud, ensures lower latency while also addresses data privacy issues. In this work, we deal with the placement of analytic tasks to heterogeneous geo-distributed edge devices while targeting three objectives, namely latency, quality of results, and resource utilization. In addition, we investigate this multi-objective problem in a multi-query setting, where we jointly optimize multiple analytic jobs while dynamically adjusting task placement decisions. We explore multiple solutions that we thoroughly evaluate; interestingly, in a multi-query setting, all three objectives can be improved simultaneously by our proposals in many cases. Furthermore, we develop a proof-of-concept prototype using Apache Storm. Our solutions are thoroughly evaluated and shown to yield improvements by more than 50% compared to advanced baselines targeting only latency. Moreover, our software prototype managed to achieve speedups of up to 6 × over the Resource Aware Apache Storm scheduler, with an average speedup of 2.76 × , when deployed over a small-scale infrastructure. [ABSTRACT FROM AUTHOR]

The superstructure spots that appear in diffraction patterns of tilted perovskites are well documented and easily calculated using crystallographic software. Here, by considering a distortion mode as a perturbation of the prototype perovskite structure, it is shown how the structure‐factor equation yields Boolean conditions for the presence of superstructure reflections. This approach may have some advantages for the analysis of electron diffraction patterns of perovskites. [ABSTRACT FROM AUTHOR]

The study of topological policy cultures highlights a tendency in policy spaces to undo the effects of topographical and cultural distances and differences. In contemporary education policy trends, such traits are present in the attempts to reimagine classroom spaces. A case in point is Future Classroom Lab (FCL), a physical classroom concept developed and spread across Europe, which promotes the use of digital technologies and divides the classroom into different functional 'zones'. We analyse FCL as a prototype that incites open exploration in the use and design of classrooms. We argue that prototypes are sometimes equally morphing into proto-practices, which are practised forms of prototypes that are in constant flux, enabling new and different functions, meanings and emotions to emerge. Prototypes and proto-practices secure the continuous transformation of policy spaces through relatively open variation, differentiation and exploration. As such, they are emblematic of contemporary topological policy cultures. [ABSTRACT FROM AUTHOR]

A two-transformer active clamp forward flyback (ACFF) converter without output inductors is suitable for high output current applications such as low-voltage DC-DC converters (LDCs) in electrified vehicles. This paper presents the reverse power transmission operation of an ACFF converter used Synchronous Rectifier (SR). One of the target applications of the proposed converter is bidirectional LDCs used in electrified vehicles due to its high-power density and cost competitiveness. Operational principles with key voltage and current waveforms are provided, and a detailed analysis of each operating interval is provided, offering guidelines for component selection. Experimental results obtained from a 14 V–600 V hardware prototype verifies the feasibility of operation in practical LDCs. [ABSTRACT FROM AUTHOR]

This paper proposes a new averaged switch model for pulse-width modulated (PWM) single-ended primary-inductor converter (SEPIC) operating in discontinuous conduction mode (DCM). The equivalent series resistance (ESR) of each energy component is considered to achieve a more precise model. The model, which is modification of the conventional averaging equation, accurately reflects both the remaining current and the actual charge on each capacitor in DCM. The proposed model utilizes a new duty ratio constraint and predicts better than previous models at high frequencies. The dependent sources of the switch components are derived from the modified averaged equation, and an implementation of the model in LTspice XVII is provided to facilitate the frequency response analysis. The frequency response of a prototype SEPIC in DCM, with an input voltage of 5 V, an output voltage of 13.5 V, and a switching frequency of 100 kHz, was experimentally measured to verify the proposed model. Simulation and experimental results demonstrate that the proposed averaged switch model solves the discrepancies at high frequencies, which was a limitation of previous models. [ABSTRACT FROM AUTHOR]

This paper proposes a smooth mode-switching method based on state trajectory control to suppress overshoot and to shorten switching time during the mode switching of LLC-C resonant converters. First, the resonant tank trajectories of the LLC and LCCL are analyzed. Second, through a transformation of the resonant tank trajectory, the optimal trajectory of the resonant tank switching is drawn. Then the switching optimization cycle time is calculated by a diagram of the optimal trajectory. Thus, the PWM conversion to the optimization cycle is controlled directly when the switching signal comes. By this control method, a smooth transition of the resonant tank voltage and current between the two modes is achieved. At last, a prototype with a rated power of 500 W is built to check the feasibility and effectiveness of the proposed switching method. Experiment results show that the current surge of the resonant tank is reduced from 12.3 to 8.6 A when the state trajectory control is applied. The voltage surge of the second resonant capacitor in parallel is reduced from 906 to 712 V. Meanwhile, the switching time is shortened by 0.21 ms, which speeds up the switching process. [ABSTRACT FROM AUTHOR]

People prefer prototypical stimuli over atypical stimuli. The dominant explanation for this prototype preference effect is that prototypical stimuli are processed more fluently. However, a more recent account proposes that prototypes are more strongly associated with their category's valence, leading to a reversed prototype preference effect for negative categories. One critical but untested assumption of this category-valence account is that no prototype preference should emerge for entirely neutral categories. We tested this prediction by conditioning categories of dot patterns positively, negatively, or neutrally. In line with previous findings on the category-valence account, prototype preference reversed for negatively conditioned categories. However, prototype preference was similarly strong for positive and neutral categories. These findings imply that prototype preferences do not only reflect a transfer of category valence to exemplars. Instead, the results suggest that prototype preference is a multi-process phenomenon arising from the activated category valence and a fluency-based process. We discuss further implications for theories on fluency and prototype preference. [ABSTRACT FROM AUTHOR]

The task of few-shot action recognition aims to recognize novel action classes using only a small number of labeled training samples. How to better describe the action in each video and how to compare the similarity between videos are two of the most critical factors in this task. Directly describing the video globally or by its individual frames cannot well represent the spatiotemporal dependencies within an action. On the other hand, naively matching the global representations of two videos is also not optimal since action can happen at different locations in a video with different speeds. In this work, we propose a novel approach that describes each video using multiple types of prototypes and then computes the video similarity with a particular matching strategy for each type of prototypes. To better model the spatiotemporal dependency, we describe the video by generating prototypes that model the multi-level spatiotemporal relations via transformers. There are a total of three types of prototypes. The first type of prototypes are trained to describe specific aspects of the action in the video e.g., the start of the action, regardless of its timestamp. These prototypes are directly matched one-to-one between two videos to compare their similarity. The second type of prototypes are the timestamp-centered prototypes that are trained to focus on specific timestamps of the video. To deal with the temporal variation of actions in a video, we apply bipartite matching to allow the matching of prototypes of different timestamps. The third type of prototypes are generated from the timestamp-centered prototypes, which regularize their temporal consistency while serving as an auxiliary summarization of the whole video. Experiments demonstrate that our proposed method achieves state-of-the-art results on multiple benchmarks. [ABSTRACT FROM AUTHOR]

As blockchain technology advances, cross-chain asset transfer has become a critical issue in achieving interoperability between different blockchain networks. However, existing cross-chain solutions often require high trust requirements and complex communication protocols, which hinder usability and flexibility. To address these issues, this work introduces the temporary relay, a novel cross-chain asset transfer model without continuous blockchain network presence and frequent inter-chain communication. Technically, the temporary relay uses non-interactive zero-knowledge proofs to verify transactions and protect privacy while ensuring blockchain immutability and traceability after the temporary relay is shut down. We detail the construction of the temporary relay and analyze the security of the circuits constructed by the zero-knowledge proofs. Prototype implementation on the Substrate blockchain platform and experimental evaluation demonstrate the feasibility of the temporary relay. Furthermore, the verification time of zero-knowledge proofs in our model is short. [ABSTRACT FROM AUTHOR]

A fractal, a self-similar organic or geometric pattern that repeats at varying scales, is one of the most compelling characteristics found in nature. Previous studies on fractal patterns have demonstrated consistent trends in potential psychological benefits, such as stress reduction. However, we fall short of understanding one of the essential properties of fractals found in nature, i.e., the three-dimensionality of their appearance. In this study, we aimed at understanding the role of the three-dimensionalization of fractal patterns in spatial structures on human subjective perceptual experience. Two hundred seventy three-dimensional spatial prototype models were created for this study, spanning two dimensions: (1) the application of spatial depth (shallow; medium; deep) and (2) fractal complexity (low; medium; high). The participants rated each space on six psychological dimensions (bad–good; stressful–relaxing; ugly–beautiful; boring–interesting; leave–enter; ignore–explore). Significant effects of the application depth of fractals were observed primarily for "boring-interesting", "ignore-explore", and "leave-enter" dimensions and were primarily manifested within spaces with medium and high D-values. The results suggest that spatial depth plays a significant role in individuals' experiences of fractal spaces, arguably by making the space more engaging and interesting. [ABSTRACT FROM AUTHOR]

Object detection is a crucial capability of autonomous agents for human–robot collaboration, as it facilitates the identification of the current processing state. In industrial scenarios, it is uncommon to have comprehensive knowledge of all the objects involved in a given task. Furthermore, training during deployment is not a viable option. Consequently, there is a need for a detector that is able to adapt to novel objects during deployment without the necessity of retraining or fine-tuning on novel data. To achieve this, we propose to exploit the ability of discriminative embeddings learned by an object re-identification model to generalize to unknown categories described by a few shots. To do so, we extract object crops with a class-agnostic detector and then compare the object features with the prototypes of the novel objects. Moreover, we demonstrate that the embedding is also effective for predicting regions of interest, which narrows the search space of the class-agnostic detector and, consequently, increases processing speed. The effectiveness of our approach is evaluated in an assembly scenario, wherein the majority of objects belong to categories distinct from those present in the training datasets. Our experiments demonstrate that, in this scenario, our approach outperforms the current best few-shot object-detection approach DE-ViT, which also does not perform fine-tuning on novel data, in terms of both detection capability and inference speed. [ABSTRACT FROM AUTHOR]

To address challenges such as low starting torque and inaccurate position estimation in traditional sensorless control methods for switched reluctance motors (SRMs), this paper proposes a sensorless control strategy suitable for the startup and low-to-medium speed operation of multiphase SRMs. Firstly, an improved inductance calculation model for the pulse injection region is proposed based on the electromagnetic characteristics of SRM. Secondly, leveraging the results of the inductance model calculation, a three-phase commutation rule is designed to enhance the starting capability. Lastly, an adaptive angle tuning (AAT) module is devised to improve the phase commutation width, and the pulse injection region is optimized through a dynamic inductance threshold method. The efficacy of the proposed method was validated through simulations conducted on a prototype six-phase 12/10 SRM. [ABSTRACT FROM AUTHOR]