Adaptive fuzzy sliding mode algorithm-based decentralised control for a permanent magnet spherical actuator

<p>The dynamic model of multi-degree-of-freedom permanent magnet (PM) spherical actuators is multivariate and nonlinear due to strong inter-axis couplings, which affects the trajectory tracking performance of the system. In this paper, a decentralised control strategy based on adaptive fuzzy sliding mode (AFSM) algorithm is developed for a PM spherical actuator to enhance its trajectory tracking performance. In this algorithm, the coupling terms are separated as subsystems from the entire system. The AFSM algorithm is applied in such a way that the fuzzy logic systems are used to approximate the subsystem with uncertainties. A sliding mode term is introduced to compensate for the effect of coupling terms and fuzzy approximation error. The stability of the proposed method is guaranteed by choosing the appropriate Lyapunov function. Both simulation and experimental results show that the proposed control algorithm can effectively handle various uncertainties and inter-axis couplings, and improve the trajectory tracking precision of the spherical actuator.</p

Tell Me What You Want: Exploring the Impact of Offering Option Repertoires on Service Performance in Gig Economy

Confronted with an increasingly competitive business landscape for credence goods in the gig economy, sellers in e-marketplaces must effectively design their services by configuring the service offering specification options to enhance the visibility of their service offerings. Motivated by the gap between the configuration of service offering specification options and its impact on service quality and sales, this study builds on the competitive repertoire theory to advance a research model that seeks to unveil how the volume, complexity, and heterogeneity of service offering specification option repertoires affect service quality and sales. We empirically examined our hypotheses with a dataset comprising 3,307 lifestyle-themed credence goods observations from Fiverr, one of the largest e-marketplaces for gig economy in the world. We discover that the repertoire volume increases both service quality and sales whereas repertoire complexity only increases service quality. Repertoire heterogeneity does not significantly impact on service quality and sales

Utility of EST-derived SSR in cultivated peanut (Arachis hypogaea L.) and Arachis wild species

<p>Abstract</p> <p>Background</p> <p>Lack of sufficient molecular markers hinders current genetic research in peanuts (<it>Arachis hypogaea </it>L.). It is necessary to develop more molecular markers for potential use in peanut genetic research. With the development of peanut EST projects, a vast amount of available EST sequence data has been generated. These data offered an opportunity to identify SSR in ESTs by data mining.</p> <p>Results</p> <p>In this study, we investigated 24,238 ESTs for the identification and development of SSR markers. In total, 881 SSRs were identified from 780 SSR-containing unique ESTs. On an average, one SSR was found per 7.3 kb of EST sequence with tri-nucleotide motifs (63.9%) being the most abundant followed by di- (32.7%), tetra- (1.7%), hexa- (1.0%) and penta-nucleotide (0.7%) repeat types. The top six motifs included AG/TC (27.7%), AAG/TTC (17.4%), AAT/TTA (11.9%), ACC/TGG (7.72%), ACT/TGA (7.26%) and AT/TA (6.3%). Based on the 780 SSR-containing ESTs, a total of 290 primer pairs were successfully designed and used for validation of the amplification and assessment of the polymorphism among 22 genotypes of cultivated peanuts and 16 accessions of wild species. The results showed that 251 primer pairs yielded amplification products, of which 26 and 221 primer pairs exhibited polymorphism among the cultivated and wild species examined, respectively. Two to four alleles were found in cultivated peanuts, while 3–8 alleles presented in wild species. The apparent broad polymorphism was further confirmed by cloning and sequencing of amplified alleles. Sequence analysis of selected amplified alleles revealed that allelic diversity could be attributed mainly to differences in repeat type and length in the microsatellite regions. In addition, a few single base mutations were observed in the microsatellite flanking regions.</p> <p>Conclusion</p> <p>This study gives an insight into the frequency, type and distribution of peanut EST-SSRs and demonstrates successful development of EST-SSR markers in cultivated peanut. These EST-SSR markers could enrich the current resource of molecular markers for the peanut community and would be useful for qualitative and quantitative trait mapping, marker-assisted selection, and genetic diversity studies in cultivated peanut as well as related <it>Arachis </it>species. All of the 251 working primer pairs with names, motifs, repeat types, primer sequences, and alleles tested in cultivated and wild species are listed in Additional File <supplr sid="S1">1</supplr>.</p> <suppl id="S1"> <title> <p>Additional File 1</p> </title> <text> <p><b>List of EST-SSR primers developed from cultivated peanut ESTs</b>. The file contains a table that lists primer names, repeat motifs, primer sequences, allele number and product length for the newly developed EST-SSR markers.</p> </text> <file name="1471-2229-9-35-S1.xls"> <p>Click here for file</p> </file> </suppl

Simultaneous Inhibition of MEK and Hh Signaling Reduces Pancreatic Cancer Metastasis

Pancreatic cancer, mostly pancreatic ductal adenocarcinoma (PDAC), is one of the most lethal cancer types, with an estimated 44,330 death in 2018 in the US alone. While targeted therapies and immune checkpoint inhibitors have significantly improved treatment options for patients with lung cancer and renal cell carcinomas, little progress has been made in pancreatic cancer, with a dismal 5-year survival rate currently at ~8%. Upon diagnosis, the majority of pancreatic cancer cases (~80%) are already metastatic. Thus, identifying ways to reduce pancreatic cancer metastasis is an unmet medical need. Furthermore, pancreatic cancer is notorious resistant to chemotherapy. While Kirsten RAt Sarcoma virus oncogene (K-RAS) mutation is the major driver for pancreatic cancer, specific inhibition of RAS signaling has been very challenging, and combination therapy is thought to be promising. In this study, we report that combination of hedgehog (Hh) and Mitogen-activated Protein/Extracellular Signal-regulated Kinase Kinase (MEK) signaling inhibitors reduces pancreatic cancer metastasis in mouse models. In mouse models of pancreatic cancer metastasis using human pancreatic cancer cells, we found that Hh target gene Gli1 is up-regulated during pancreatic cancer metastasis. Specific inhibition of smoothened signaling significantly altered the gene expression profile of the tumor microenvironment but had no significant effects on cancer metastasis. By combining Hh signaling inhibitor BMS833923 with RAS downstream MEK signaling inhibitor AZD6244, we observed reduced number of metastatic nodules in several mouse models for pancreatic cancer metastasis. These two inhibitors also decreased cell proliferation significantly and reduced CD45⁺ cells (particularly Ly6G⁺CD11b⁺ cells). We demonstrated that depleting Ly6G⁺ CD11b⁺ cells is sufficient to reduce cancer cell proliferation and the number of metastatic nodules. In vitro, Ly6G⁺ CD11b⁺ cells can stimulate cancer cell proliferation, and this effect is sensitive to MEK and Hh inhibition. Our studies may help design novel therapeutic strategies to mitigate pancreatic cancer metastasis

Unraveling the Effects of Mobile Application Usage on Users’ Health Status: Insights from Conservation of Resources Theory

Numerous studies have documented adverse consequences arising from increased technology usage and advocated for a reduction in such usage as a plausible remedy. However, such recommendations are often infeasible and oversimplistic given mounting evidence attesting to users’ growing reliance on technology in both their personal and professional lives. Building on conservation of resources (COR) theory, we construct a research model to explain how mobile application usage, as delineated by its breadth and depth, affects users’ nomophobia and sleep deprivation, which can have negative impacts on users’ health status. We also consider the moderating influence of physical activity in mitigating the effects of mobile application usage on users’ health. We validated our hypotheses via data collected by surveying 5,842 respondents. Empirical findings reveal that (1) nomophobia is positively influenced by mobile application usage breadth but negatively influenced by mobile application usage depth, (2) sleep deprivation is negatively influenced by mobile application usage breadth but positively influenced by mobile application usage depth, and (3) sleep deprivation and nomophobia negatively impact users’ health status, whereas (4) physical activity attenuates the impact of mobile application usage on sleep deprivation but not nomophobia. The findings from this study not only enrich the extant literature on the health outcomes of mobile application usage by unveiling the impact of mobile application usage patterns and physical activity on users’ health but they also inform practitioners on how calibrating usage breadth and depth, along with encouraging physical activity, can promote healthy habits among users

The taxonomic relevance of flower colour for Epimedium (Berberidaceae), with morphological and nomenclatural notes for five species from China

Morphological variations, particularly flower colour, could be considered as an evolutionarily and ornamentally significant taxonomic criterion for Epimedium. Our extensive field investigation based on population studies revealed abundant intraspecific variations in flower colour. Five species, (i.e., E. acuminatum Franch., E. leptorrhizum Stearn, E. pauciflorum K.C.Yen, E. mikinorii Stearn, and E. glandulosopilosum H.R.Liang) were found to possess polymorphic flower colour, which is first described and illustrated here. Moreover, all these species were found to be polymorphic in other diagnostic characters, such as the type of rhizome, the number and arrangement of stem-leaves, and/or their indumentum, which have not been adequately described in previous studies. Therefore, their morphological descriptions have been complemented and/or revised. We also provide notes on the morphology and nomenclature for each species. Additionally, a key to the species in China has been provided. The present study could serve as a basis for understanding their taxonomy and helping their utilisation as an ornamental plant

The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions

Ambulatory impairments; Machine learning; Multiple sclerosisDeficiencias ambulatorias; Aprendizaje automático; Esclerosis múltipleDeficiències ambulatòries; Aprenentatge automàtic; Esclerosi múltipleAbstract Background and objectives Multiple sclerosis (MS) is a progressive inflammatory and neurodegenerative disease of the central nervous system affecting over 2.5 million people globally. In-clinic six-minute walk test (6MWT) is a widely used objective measure to evaluate the progression of MS. Yet, it has limitations such as the need for a clinical visit and a proper walkway. The widespread use of wearable devices capable of depicting patients’ activity profiles has the potential to assess the level of MS-induced disability in free-living conditions. Methods In this work, we extracted 96 features in different temporal granularities (from minute-level to day-level) from wearable data and explored their utility in estimating 6MWT scores in a European (Italy, Spain, and Denmark) MS cohort of 337 participants over an average of 10 months’ duration. We combined these features with participants’ demographics using three regression models including elastic net, gradient boosted trees and random forest. In addition, we quantified the individual feature's contribution using feature importance in these regression models, linear mixed-effects models, generalized estimating equations, and correlation-based feature selection (CFS). Results The results showed promising estimation performance with R2 of 0.30, which was derived using random forest after CFS. This model was able to distinguish the participants with low disability from those with high disability. Furthermore, we observed that the minute-level (≤ 8 minutes) step count, particularly those capturing the upper end of the step count distribution, had a stronger association with 6MWT. The use of a walking aid was indicative of ambulatory function measured through 6MWT. Conclusions This study demonstrates the utility of wearables devices in assessing ambulatory impairments in people with MS in free-living conditions and provides a basis for future investigation into the clinical relevance.The RADAR-CNS project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115902. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA, www.imi.europa.eu. This paper reflects the views of the RADAR-CNS consortium and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein. The funding body have not been involved in the design of the study, the collection or analysis of data, or the interpretation of data. RJBD is supported by the following: (1) NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK; (2) Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome Trust; (3) The BigData@Heart Consortium, funded by the Innovative Medicines Initiative-2 Joint Undertaking under grant agreement No. 116074. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA; it is chaired by DE Grobbee and SD Anker, partnering with 20 academic and industry partners and ESC; (4) the National Institute for Health Research University College London Hospitals Biomedical Research Centre; (5) the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London; (6) the UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare; (7) the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHS Foundation Trust