A micro electromagnetic generator for vibration energy harvesting

Vibration energy harvesting is receiving a considerable amount of interest as a means for powering wireless sensor nodes. This paper presents a small (component volume 0.1 cm3, practical volume 0.15 cm3) electromagnetic generator utilizing discrete components and optimized for a low ambient vibration level based upon real application data. The generator uses four magnets arranged on an etched cantilever with a wound coil located within the moving magnetic field. Magnet size and coil properties were optimized, with the final device producing 46 µW in a resistive load of 4 k? from just 0.59 m s-2 acceleration levels at its resonant frequency of 52 Hz. A voltage of 428 mVrms was obtained from the generator with a 2300 turn coil which has proved sufficient for subsequent rectification and voltage step-up circuitry. The generator delivers 30% of the power supplied from the environment to useful electrical power in the load. This generator compares very favourably with other demonstrated examples in the literature, both in terms of normalized power density and efficiency

Multi-channel Transformers for Multi-articulatory Sign Language Translation

Sign languages use multiple asynchronous information channels (articulators), not just the hands but also the face and body, which computational approaches often ignore. In this paper we tackle the multi-articulatory sign language translation task and propose a novel multi-channel transformer architecture. The proposed architecture allows both the inter and intra contextual relationships between different sign articulators to be modelled within the transformer network itself, while also maintaining channel specific information. We evaluate our approach on the RWTH-PHOENIX-Weather-2014T dataset and report competitive translation performance. Importantly, we overcome the reliance on gloss annotations which underpin other state-of-the-art approaches, thereby removing future need for expensive curated datasets

Development of a biomechanical energy harvester

© 2009 Li et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Incentivizing the Use of Quantified Self Devices: The Cases of Digital Occupational Health Programs and Data-Driven Health Insurance Plans

Initially designed for a use in private settings, smartwatches, activity trackers and other quantified self devices are receiving a growing attention from the organizational environment. Firms and health insurance companies, in particular, are developing digital occupational health programs and data-driven health insurance plans centered around these systems, in the hope of exploiting their potential to improve individual health management, but also to gather large quantities of data. As individual participation in such organizational programs is voluntary, organizations often rely on motivational incentives to prompt engagement. Yet, little is known about the mechanisms employed in organizational settings to incentivize the use of quantified self devices. We therefore seek, in this exploratory paper, to offer a first structured overview of this topic and identify the main motivational incentives in two emblematical cases: digital occupational health programs and data-driven health insurance plans. By doing so, we aim to specify the nature of this new dynamic around the use of quantified self devices and define some of the key lines for further investigation

Recognition of Crowd Behavior from Mobile Sensors with Pattern Analysis and Graph Clustering Methods

Mobile on-body sensing has distinct advantages for the analysis and understanding of crowd dynamics: sensing is not geographically restricted to a specific instrumented area, mobile phones offer on-body sensing and they are already deployed on a large scale, and the rich sets of sensors they contain allows one to characterize the behavior of users through pattern recognition techniques. In this paper we present a methodological framework for the machine recognition of crowd behavior from on-body sensors, such as those in mobile phones. The recognition of crowd behaviors opens the way to the acquisition of large-scale datasets for the analysis and understanding of crowd dynamics. It has also practical safety applications by providing improved crowd situational awareness in cases of emergency. The framework comprises: behavioral recognition with the user's mobile device, pairwise analyses of the activity relatedness of two users, and graph clustering in order to uncover globally, which users participate in a given crowd behavior. We illustrate this framework for the identification of groups of persons walking, using empirically collected data. We discuss the challenges and research avenues for theoretical and applied mathematics arising from the mobile sensing of crowd behaviors

Strategies to improve palatability and increase consumption intentions for Momordica charantia (bitter melon): A vegetable commonly used for diabetes management

<p>Abstract</p> <p>Background</p> <p>Although beneficial to health, dietary phytonutrients are bitter, acid and/or astringent in taste and therefore reduce consumer choice and acceptance during food selection. <it>Momordica charantia</it>, commonly known as bitter melon has been traditionally used in Ayurvedic and Chinese medicine to treat diabetes and its complications. The aim of this study was to develop bitter melon-containing recipes and test their palatability and acceptability in healthy individuals for future clinical studies.</p> <p>Methods</p> <p>A cross-sectional sensory evaluation of bitter melon-containing ethnic recipes was conducted among 50 healthy individuals. The primary endpoints assessed in this analysis were current consumption information and future intentions to consume bitter melon, before and after provision of attribute- and health-specific information. A convenience sample of 50, self-reported non-diabetic adults were recruited from the University of Hawaii. Sensory evaluations were compared using two-way ANOVA, while differences in stage of change (SOC) before and after receiving health information were analyzed by Chi-square (χ²) analyses.</p> <p>Results</p> <p>Our studies indicate that tomato-based recipes were acceptable to most of the participants and readily acceptable, as compared with recipes containing spices such as curry powder. Health information did not have a significant effect on willingness to consume bitter melon, but positively affected the classification of SOC.</p> <p>Conclusions</p> <p>This study suggests that incorporating bitter foods in commonly consumed food dishes can mask bitter taste of bitter melon. Furthermore, providing positive health information can elicit a change in the intent to consume bitter melon-containing dishes despite mixed palatability results.</p

Induction of beta defensin 2 by NTHi requires TLR2 mediated MyD88 and IRAK-TRAF6-p38MAPK signaling pathway in human middle ear epithelial cells

<p>Abstract</p> <p>Background</p> <p>All mucosal epithelia, including those of the tubotympanium, are secreting a variety of antimicrobial innate immune molecules (AIIMs). In our previous study, we showed the bactericidal/bacteriostatic functions of AIIMs against various otitis media pathogens. Among the AIIMs, human β-defensin 2 is the most potent molecule and is inducible by exposure to inflammatory stimuli such as bacterial components or proinflammatory cytokines. Even though the β-defensin 2 is an important AIIM, the induction mechanism of this molecule has not been clearly established. We believe that this report is the first attempt to elucidate NTHi induced β-defensin expression in airway mucosa, which includes the middle ear.</p> <p>Methods</p> <p>Monoclonal antibody blocking method was employed in monitoring the TLR-dependent NTHi response. Two gene knock down methods – dominant negative (DN) plasmid and small interfering RNA (siRNA) – were employed to detect and confirm the involvement of several key genes in the signaling cascade resulting from the NTHi stimulated β-defensin 2 expression in human middle ear epithelial cell (HMEEC-1). The student's <it>t</it>-test was used for the statistical analysis of the data.</p> <p>Results</p> <p>The experimental results showed that the major NTHi-specific receptor in HMEEC-1 is the Toll-like receptor 2 (TLR2). Furthermore, recognition of NTHi component(s)/ligand(s) by TLR2, activated the Toll/IL-1 receptor (TIR)-MyD88-IRAK1-TRAF6-MKK3/6-p38 MAPK signal transduction pathway, ultimately leading to the induction of β-defensin 2.</p> <p>Conclusion</p> <p>This study found that the induction of β-defensin 2 is highest in whole cell lysate (WCL) preparations of NTHi, suggesting that the ligand(s) responsible for this up-regulation may be soluble macromolecule(s). We also found that this induction takes place through the TLR2 dependent MyD88-IRAK1-TRAF6-p38 MAPK pathway, with the primary response occurring within the first hour of stimulation. In combination with our previous studies showing that IL-1α-induced β-defensin 2 expression takes place through a MyD88-independent Raf-MEK1/2-ERK MAPK pathway, we found that both signaling cascades act synergistically to up-regulate β-defensin 2 levels. We propose that this confers an essential evolutionary advantage to the cells in coping with infections and may serve to amplify the innate immune response through paracrine signaling.</p

Nontypable Haemophilus influenzae Displays a Prevalent Surface Structure Molecular Pattern in Clinical Isolates

Non-typable Haemophilus influenzae (NTHi) is a Gram negative pathogen that causes acute respiratory infections and is associated with the progression of chronic respiratory diseases. Previous studies have established the existence of a remarkable genetic variability among NTHi strains. In this study we show that, in spite of a high level of genetic heterogeneity, NTHi clinical isolates display a prevalent molecular feature, which could confer fitness during infectious processes. A total of 111 non-isogenic NTHi strains from an identical number of patients, isolated in two distinct geographical locations in the same period of time, were used to analyse nine genes encoding bacterial surface molecules, and revealed the existence of one highly prevalent molecular pattern (lgtF+, lic2A+, lic1D+, lic3A+, lic3B+, siaA−, lic2C+, ompP5+, oapA+) displayed by 94.6% of isolates. Such a genetic profile was associated with a higher bacterial resistance to serum mediated killing and enhanced adherence to human respiratory epithelial cells

Sap Transporter Mediated Import and Subsequent Degradation of Antimicrobial Peptides in Haemophilus

Antimicrobial peptides (AMPs) contribute to host innate immune defense and are a critical component to control bacterial infection. Nontypeable Haemophilus influenzae (NTHI) is a commensal inhabitant of the human nasopharyngeal mucosa, yet is commonly associated with opportunistic infections of the upper and lower respiratory tracts. An important aspect of NTHI virulence is the ability to avert bactericidal effects of host-derived antimicrobial peptides (AMPs). The Sap (sensitivity to antimicrobial peptides) ABC transporter equips NTHI to resist AMPs, although the mechanism of this resistance has remained undefined. We previously determined that the periplasmic binding protein SapA bound AMPs and was required for NTHI virulence in vivo. We now demonstrate, by antibody-mediated neutralization of AMP in vivo, that SapA functions to directly counter AMP lethality during NTHI infection. We hypothesized that SapA would deliver AMPs to the Sap inner membrane complex for transport into the bacterial cytoplasm. We observed that AMPs localize to the bacterial cytoplasm of the parental NTHI strain and were susceptible to cytoplasmic peptidase activity. In striking contrast, AMPs accumulated in the periplasm of bacteria lacking a functional Sap permease complex. These data support a mechanism of Sap mediated import of AMPs, a novel strategy to reduce periplasmic and inner membrane accumulation of these host defense peptides