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In prior literature, online endorsement system allowing the users to “like” or “dislike” shared information is found very useful in information filtering and trust elicitation in most social networks. This paper shows that such systems could fail in the context of investment communities due to several psychological biases.

This study develops a series of regression analyses to model the “like”/“dislike” voting process and whether or not such endorsement distinguishes between valuable information and noise. Trading simulations are also used to validate the practical implications of the findings.

The main findings of this research are twofold: (1) in the context of investment communities, online endorsement system fails to signify value-relevant information and (2) bullish information and “wisdom over the past event” information receive more “likes” and fewer “dislikes” on average, but they underperform in stock market price discovery.

This study demonstrates that biased endorsement may lead to the failure of the online endorsement system as information gatekeeper in investment communities. Two underlying mechanisms are proposed and tested. This study opens up new research opportunities to investigate the causes of biased endorsement in online environment and motivates the development of alternative information filtering systems.

Simulations exist for the prediction of the behaviour of building structural systems under fire, including two-way coupled fire-structure interaction. However, these simulations do not include detailed models of the connections, whereas these connections may impact the overall behaviour of the structure. Therefore, this paper proposes a two-scale method to include screw connections.

The two-scale method consists of (a) a global-scale model that models the overall structural system and (b) a small-scale model to describe a screw connection. Components in the global-scale model are connected by a spring element instead of a modelled screw, and the stiffness of this spring element is predicted by the small-scale model, updated at each load step. For computational efficiency, the small-scale model uses a proprietary technique to model the behaviour of the threads, verified by simulations that model the complete thread geometry, and validated by existing pull-out experiments. For four screw failure modes, load-deformation behaviour and failure predictions of the two-scale method are verified by a detailed system model. Additionally, the two-scale method is validated for a combined load case by existing experiments, and demonstrated for different temperatures. Finally, the two-scale method is illustrated as part of a two-way coupled fire-structure simulation.

It was shown that proprietary ”threaded connection interaction” can predict thread relevant failure modes, i.e. thread failure, shank tension failure, and pull-out. For bearing, shear, tension, and pull-out failure, load-deformation behaviour and failure predictions of the two-scale method correspond with the detailed system model and Eurocode predictions. Related to combined load cases, for a variety of experiments a good correlation has been found between experimental and simulation results, however, pull-out simulations were shown to be inconsistent.

More research is needed before the two-scale method can be used under all conditions. This relates to the failure criteria for pull-out, combined load cases, and temperature loads.

The two-scale method bridges the existing very detailed small-scale screw models with present global-scale structural models, that in the best case only use springs. It shows to be insightful, for it contains a functional separation of scales, revealing their relationships, and it is computationally efficient as it allows for distributed computing. Furthermore, local small-scale non-convergence (e.g. a screw failing) can be handled without convergence problems in the global-scale structural model.

Stitching is the traditional method of creating seams using needles and threads. However, this is not useful for waterproof breathable garments as needle holes allow water to penetrate inside the garment, compromising its functionality. This study aims to investigate different techniques for covering the needle holes formed during stitching to achieve a seam that is waterproof, durable and functionally effective.

This study investigates different methods to cover needle holes formed during stitching with the help of seam tape, seam grip adhesive and fuser thread. The emphasis is on evaluating the seam characteristics, including seam strength, seam efficiency, puckering, bending stiffness and resistance to water penetration. Statistical analysis involves the use of the Shapiro–Wilk test, Levene statistic, one-way ANOVA and Tukey’s HSD and Tamhane post-hoc tests.

The experimental results suggest that seam tape is effective in enhancing water resistance, seam strength and seam efficiency, but it contributes to stiffness and aesthetically degrades seams due to increased puckering. Meanwhile, the use of fuser thread presents an alternative, exhibiting improved waterproof properties compared to regular stitching. It offers more flexibility and less puckering compared to seam tape.

This study contributes novel insights by shifting the focus from alternative seaming methods such as bonding and welding, to enhancing traditional stitching for waterproof seam construction. While prior research primarily explored alternatives to stitching, this study uniquely addresses the effectiveness of different techniques in covering needle holes to achieve waterproof seams. The findings provide valuable information for enhancing the functionality of stitched seams in the production of waterproof breathable garments.

The author aims to walk beside the singular privileged class of White women’s suffrage feminist origin story to (re)construct plausible feminist fragmented threads as antenarratives in the context of business management education. To accomplish this (re)assembling of threads, the author examined two North American business trade publications created and used within two business schools, Harvard University’s Harvard Business Review (HBR), established in 1922, and Western University’s The Quarterly Review of Commerce (The Quarterly), established in 1933.

The author carefully reviewed almost 4,000 articles from HBR and The Quarterly, focusing on 308 articles that addressed the experiences of complex women. With this subset of collected articles, the author highlighted overlooked details, accidents and errors, generating interest and curiosity about the emergence of these fragmented and paradoxical origins that align with Foucault's histories of errors. By grouping these narrative fragments into themes and conducting a critical discourse analysis that incorporated influences from the external environment, the author reconstructed plural feminist origins antenarratives.

The themes discovered, including women as consumers, explicit working women concerns, women as authors/coauthors, diversity and social justice initiatives, and women in higher education/training, are not merely descriptive observations. They are the building blocks for identifying and analyzing the power relations circulating among feminist origins antenarratives within management education circles. These antenarratives include shedding light on women working in capitalist contexts, the educational needs of business women, and men and naming (but not breaking) the “mythologies” of women at work. These findings are transformative to the understanding of plural feminist origins.

The uniqueness of this work lies in its threefold contributions: moving away from the notion of a singular feminist origin story and instead embracing the complexity of multiple, paradoxical and incomplete origins; shedding light on the spectrum of power relations – ranging from productive to oppressive – that shaped the experiences of women in two management educational circles during the first half of the 20th century; and introducing the concept of inflection points, which underscores the fluidity of knowledge.

This study aims to extend the known design guidelines for the polymer-based fused filament fabrication (FFF) 3D printing process with the focus on function-integrated components, specifically optomechanical parts. The potential of this approach is demonstrated by manufacturing function-integrated optomechanics for a low-power solid-state laser system.

For the production of function-integrated additively manufactured optomechanics using the FFF process, essential components and subsystems have been identified for which no design guidelines are available. This includes guidelines for integrating elements, particularly optics, into a polymer structure as well as guidelines for printing functional threads and ball joints. Based on these results, combined with prior research, a function-integrated low-power solid-state laser optomechanic was fabricated via the FFF process, using a commercial 3D printer of the type Ultimaker 3. The laser system's performance was assessed and compared to a reference system that employed commercial optomechanics, additionally confirming the design guidelines derived from the study.

Based on the design goal of function integration, the existing design guidelines for the FFF process are systematically extended. This success is demonstrated by the fabrication of an integrated optomechanic for a solid-state laser system.

Based on these results, scientists and engineers will be able to use the FFF process more extensively and benefit from the possibilities of function-integrated manufacturing.

Extensive research has been published on additive manufacturing of optomechanics. However, this research often emphasizes only cost reduction and short-term availability of components by reprinting existing parts. This paper aims to explore the capabilities of additive manufacturing in the production of function-integrated components to reduce the number of individual parts required, thereby decreasing the workload for system assembly and leading to an innovative production process for optical systems. Consequently, where needed, it provides new design guidelines or extends existing ones and verifies them by means of test series.

This exploratory, descriptive study examines the factors that might influence the success or failure of online peer production communities during their inception stage. It focuses on community-building activities, the roles of users and the dynamics of user interaction, aiming to shed light on practices that could contribute to a community's success at the inception stage.

By comparing two Stack Exchange Q&A communities with the same timelines but opposite outcomes during their beta testing phases, the research utilizes quantitative methods to categorize community activities, define user roles via k-means cluster analysis and examine interaction networks using social network analysis.

Our findings suggest the successful Mathematics Q&A community exhibited several distinct practices during its inception, such as the utilization of both external and internal tools, the development of community-specific tutorials and the strategic use of flagging functions for moderation. Eight user roles were discerned, with roles like content editors, metadata curators and gatekeepers being particularly prominent in the successful community. Additionally, a more densely interconnected user network characterized by active participation was observed in the successful community.

Concentrating on the inception stage of online communities, this study uncovers insights into the dynamics at play in the early life of peer production environments and provides empirical observations that may assist in shaping strategies for new online communities. It stands out by comparing communities within the same period to understand factors that may influence their early success.

Traditional visual simultaneous localization and mapping (SLAM) systems are primarily based on the assumption that the environment is static, which makes them struggle with the interference caused by dynamic objects in complex industrial production environments. This paper aims to improve the stability of visual SLAM in complex dynamic environments through semantic segmentation and its optimization.

This paper proposes a real-time visual SLAM system for complex dynamic environments based on YOLOv5s semantic segmentation, named YLS-SLAM. The system combines semantic segmentation results and the boundary semantic enhancement algorithm. By recognizing and completing the semantic masks of dynamic objects from coarse to fine, it effectively eliminates the interference of dynamic feature points on the pose estimation and enhances the retention and extraction of prominent features in the background, thereby achieving stable operation of the system in complex dynamic environments.

Experiments on the Technische Universität München and Bonn data sets show that, under monocular and Red, Green, Blue - Depth modes, the localization accuracy of YLS-SLAM is significantly better than existing advanced dynamic SLAM methods, effectively improving the robustness of visual SLAM. Additionally, the authors also conducted tests using a monocular camera in a real industrial production environment, successfully validating its effectiveness and application potential in complex dynamic environment.

This paper combines semantic segmentation algorithms with boundary semantic enhancement algorithms to effectively achieve precise removal of dynamic objects and their edges, while ensuring the system's real-time performance, offering significant application value.

The device, amplifies and sub-regionally transmits the current generated by the body temperature thermoelectric generator through a smart body temperature sensor.

The present study designs a wearable smart device regarding the relationship between temperature and emotion.

Experimental results show that the device can accurately detect changes in human body temperature under hilarious, fearful, soothing and angry emotions, so as to achieve changes in clothing colors, namely blue, red, green and brown.

Different areas of clothing produce controllable and intelligent color, so that adult emotions can be understood through changes in clothing colors, which is conducive to judging their moods and promoting social interaction.