36,457 research outputs found
Application of Multichannel Active Vibration Control in a Multistage Gear Transmission System
Gears are the most important parts of rotating machinery and power transmission devices. When gears are engaged in meshing transmission, vibration will occur due to factors such as gear machining errors, meshing rigidity, and meshing impact. The traditional FxLMS algorithm, as a common active vibration algorithm, has been widely studied and applied in gear transmission system active vibration control in recent years. However, it is difficult to achieve good performance in convergence speed and convergence precision at the same time. This paper proposes a variable-step-size multichannel FxLMS algorithm based on the sampling function, which accelerates the convergence speed in the initial stage of iteration, improves the convergence accuracy in the steady-state adaptive stage, and makes the modified algorithm more robust. Simulations verify the effectiveness of the algorithm. An experimental platform for active vibration control of the secondary gear transmission system is built. A piezoelectric actuator is installed on an additional gear shaft to form an active structure and equipped with a signal acquisition system and a control system; the proposed variable-step-size multichannel FxLMS algorithm is experimentally verified. The experimental results show that the proposed multichannel variable-step-size FxLMS algorithm has more accurate convergence accuracy than the traditional FxLMS algorithm, and the convergence accuracy can be increased up to 123%
Application of lactic acid bacteria for the biopreservation of meat products: A systematic review
.The increasing concern of consumers about food quality and safety and their rejection of chemical additives has promoted the breakthrough of the biopreservation field and the development of studies on the use of beneficial bacteria and their metabolites as potential natural antimicrobials for shelf life extension and enhanced food safety. Control of foodborne pathogens in meat and meat products represents a serious challenge for the food industry which can be addressed through the intelligent use of bio-compounds or biopreservatives. This article aims to systematically review the available knowledge about biological strategies based on the use of lactic acid bacteria to control the proliferation of undesirable microorganisms in different meat products. The outcome of the literature search evidenced the potential of several strains of lactic acid bacteria and their purified or semi-purified antimicrobial metabolites as biopreservatives in meat products for achieving longer shelf life or inhibiting spoilage and pathogenic bacteria, especially when combined with other technologies to achieve a synergistic effect.S
Analysis of reliable deployment of TDOA local positioning architectures
.Local Positioning Systems (LPS) are supposing an attractive research topic over the last few years. LPS are ad-hoc deployments of wireless sensor networks for particularly adapt to the environment characteristics in harsh environments. Among LPS, those based on temporal measurements stand out for their trade-off among accuracy, robustness and costs. But, regardless the LPS architecture considered, an optimization of the sensor distribution is required for achieving competitive results. Recent studies have shown that under optimized node distributions, time-based LPS cumulate the bigger error bounds due to synchronization errors. Consequently, asynchronous architectures such as Asynchronous Time Difference of Arrival (A-TDOA) have been recently proposed. However, the A-TDOA architecture supposes the concentration of the time measurement in a single clock of a coordinator sensor making this architecture less versatile. In this paper, we present an optimization methodology for overcoming the drawbacks of the A-TDOA architecture in nominal and failure conditions with regards to the synchronous TDOA. Results show that this optimization strategy allows the reduction of the uncertainties in the target location by 79% and 89.5% and the enhancement of the convergence properties by 86% and 33% of the A-TDOA architecture with regards to the TDOA synchronous architecture in two different application scenarios. In addition, maximum convergence points are more easily found in the A-TDOA in both configurations concluding the benefits of this architecture in LPS high-demanded applicationS
The effects of cultural dimensions on algorithmic news: How do cultural value orientations affect how people perceive algorithms?
How do cultural values influence/are influenced by algorithms? A comparative study was conducted between the United States (US) and the United Arab Emirates (UAE) to investigate how users in the different cultures perceive the features of chatbot-driven news and how they view ethical issues concerning chatbot journalism. Different models of chatbot news perception reveal that the acceptance of chatbots involves a cultural dimension as the algorithms reflect the values and interests of their constituencies. How users perceive chatbot news and how they consume and interact with the chatbots depend on the cultural and social contexts in which the interaction is taking place. Our results suggest the algorithms reflect cultural values and algorithms are implicitly situated in social contexts, mediated by cultural artifacts and activities. The results resonate with ongoing debates on whether and how algorithms reinforce cultural and social values implying the co-evolving nature of algorithms and humans
Network Slicing for Industrial IoT and Industrial Wireless Sensor Network: Deep Federated Learning Approach and Its Implementation Challenges
5G networks are envisioned to support heterogeneous Industrial IoT (IIoT) and Industrial Wireless Sensor Network (IWSN) applications with a multitude Quality of Service (QoS) requirements. Network slicing is being recognized as a beacon technology that enables multi-service IIoT networks. Motivated by the growing computational capacity of the IIoT and the challenges of meeting QoS, federated reinforcement learning (RL) has become a propitious technique that gives out data collection and computation tasks to distributed network agents. This chapter discuss the new federated learning paradigm and then proposes a Deep Federated RL (DFRL) scheme to provide a federated network resource management for future IIoT networks. Toward this goal, the DFRL learns from Multi-Agent local models and provides them the ability to find optimal action decisions on LoRa parameters that satisfy QoS to IIoT virtual slice. Simulation results prove the effectiveness of the proposed framework compared to the early tools
Advantages of Ion Mobility Coupled with HPLC/UPLC
Ion mobility is a new separation technique that can be coupled with high performance liquid chromatography (HPLC) or ultra-performance liquid chromatography (UPLC). Variances in cross-sectional ionic areas of different molecules create differential speeds through a gas allowing for millisecond separations. Combining ion mobility with both liquid chromatography and mass spectrometry with fragmentation, separations can be achieved on the second (HPLC), millisecond (ion mobility), and microsecond (mass spectrometry) timescales. This orthogonal separation greatly cleans up mass spectral data of co-eluting peaks from the liquid chromatography and adds to the descriptive data of each ion. With descriptive data such as retention time, cross-sectional area, m/z ratio, and mass spectral fragmentation, many options become available for analytical analysis. Options ranging from descriptive data collation into instrument libraries to sensitivity enhancement for trace analysis will be explored in this chapter along with the description of different forms of ion mobility
Unraveling the effect of sex on human genetic architecture
Sex is arguably the most important differentiating characteristic in most mammalian
species, separating populations into different groups, with varying behaviors, morphologies,
and physiologies based on their complement of sex chromosomes, amongst other factors. In
humans, despite males and females sharing nearly identical genomes, there are differences
between the sexes in complex traits and in the risk of a wide array of diseases. Sex provides
the genome with a distinct hormonal milieu, differential gene expression, and environmental
pressures arising from gender societal roles. This thus poses the possibility of observing
gene by sex (GxS) interactions between the sexes that may contribute to some of the
phenotypic differences observed. In recent years, there has been growing evidence of GxS,
with common genetic variation presenting different effects on males and females. These
studies have however been limited in regards to the number of traits studied and/or
statistical power. Understanding sex differences in genetic architecture is of great
importance as this could lead to improved understanding of potential differences in
underlying biological pathways and disease etiology between the sexes and in turn help
inform personalised treatments and precision medicine.
In this thesis we provide insights into both the scope and mechanism of GxS across the
genome of circa 450,000 individuals of European ancestry and 530 complex traits in the UK
Biobank. We found small yet widespread differences in genetic architecture across traits
through the calculation of sex-specific heritability, genetic correlations, and sex-stratified
genome-wide association studies (GWAS). We further investigated whether sex-agnostic
(non-stratified) efforts could potentially be missing information of interest, including sex-specific trait-relevant loci and increased phenotype prediction accuracies. Finally, we
studied the potential functional role of sex differences in genetic architecture through sex
biased expression quantitative trait loci (eQTL) and gene-level analyses.
Overall, this study marks a broad examination of the genetics of sex differences. Our findings
parallel previous reports, suggesting the presence of sexual genetic heterogeneity across
complex traits of generally modest magnitude. Furthermore, our results suggest the need to
consider sex-stratified analyses in future studies in order to shed light into possible sex-specific molecular mechanisms
Micro-Prudential Regulation and Loan Monitoring
We evaluate the value of loan monitoring systems for a bank controlled by a micro-prudential regulator. We investigate dynamic systems (an information channel that generates information flow about quality) and static systems (where the lender receives a single signal about loan quality). We find that dynamic systems carry a regulatory charge that dominates the benefit of the systems and are therefore unprofitable, whereas static systems have positive value. Specifically, lenders can profitably dismantle their dynamic systems and instead turn to static monitoring systems. The model reveals, therefore, a potential weakness of micro-prudential regulation
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Drivers and Direct Impacts of Lean Mass Dynamics on the Stopover Ecology and Migratory Pace of Nearctic-Neotropical Migrant Songbirds in Spring
Annual migration in songbirds is one of the most demanding life-history stages. It represents a period of high mortality, yet there is still much unknown about the ecological correlates that influence its successful completion. After long non-stop migratory flights, birds require a stopover period to rest and replenish depleted energy reserves. Birds use fat as the primary fuel to power long-distance flights. However, birds also burn lean tissue, which results in significant reductions in muscle and organ masses. The discovery and quantification of lean mass catabolism represented a paradigm shift in migration ecology because non-fat components were thought to remain homeostatic. Because rebuilding protein is slow, muscle and organ breakdown during migration may dramatically prolong stopover periods and delay overall migration time, which in turn dramatically reduces breeding success. Therefore, the breakdown of lean tissue, the conditions that lead to it, and its consequences are important considerations in understanding the migration strategies of birds.
Through this dissertation research, I aim to understand the impact of weather on body condition and how physiological condition impacts subsequent migratory performance. I investigate (1) how weather impacts the lean mass of songbirds after crossing an ecological barrier, and (2) how body condition after crossing an ecological barrier affects stopover duration, refueling rate, and habitat use. My predictions are that higher nightly temperatures or drier conditions experienced during migratory flight will correspond with lower lean body mass on arrival; and that birds with lower lean body mass will require longer stopovers, different habitat, or higher foraging effort to continue migration.
I used an integrative approach, combining the field and lab, to better understand how weather experienced during flight can impact the body condition of migratory birds and how this can influence the entire migratory cycle. By using Quantitative Magnetic Resonance (QMR) technology in combination with a novel automated radio-telemetry system, my research provides unprecedented access to detailed physiological and movement data for small migratory songbirds. This research underlines that successfully crossing the Gulf of Mexico may be a key driver of physiological and morphological adaptations. My findings challenge the current paradigm that birds with low lean mass require longer stopover and demonstrates that species under time constraints may shorten stopover even when in poor condition, departing in sub-optimal body condition
Interactive Sonic Environments: Sonic artwork via gameplay experience
The purpose of this study is to investigate the use of video-game technology in the design and implementation of interactive sonic centric artworks, the purpose of which is to create and contribute to the discourse and understanding of its effectiveness in electro-acoustic composition highlighting the creative process. Key research questions include: How can the language of electro-acoustic music be placed in a new framework derived from videogame aesthetics and technology? What new creative processes need to be considered when using this medium? Moreover, what aspects of 'play' should be considered when designing the systems? The findings of this study assert that composers and sonic art practitioners need little or no coding knowledge to create exciting applications and the myriad of options available to the composer when using video-game technology is limited only by imagination. Through a cyclic process of planning, building, testing and playing these applications the project revealed advantages and unique sonic opportunities in comparison to other sonic art installations. A portfolio of selected original compositions, both fixed and open are presented by the author to complement this study. The commentary serves to place the work in context with other practitioners in the field and to provide compositional approaches that have been taken
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