Driving Individuals’ Subjective Wellbeing in Virtual Communities through Interpersonal and Impersonal Mechanisms

In this study, we integrate different research streams—attachment, social identity, and organizational citizenship behavior—to have a better understanding of determinants of individual subjective wellbeing in the context of a virtual community (VC). Attachment is an emotion-laden, target-specific bond between a person and a specific object. Attachment is an important predictor of citizenship behavior, and therefore an important aspect to understand and to enhance in order to promote citizenship behavior. We identify two broad categories of virtual community citizenship behavior: citizenship behaviors directed toward benefitting other individuals (VCCBI), and citizenship behaviors directed toward benefitting the VC (VCCBC). We also identify two distinct attachments: emotional bonds among community members and emotional bonds to the community identity. This study proposes a dual attachment model in which subjective wellbeing is driven mainly by two mechanisms: (1) the interpersonal-based mechanism which relates common bond attachment to VCCBI and subjective wellbeing, and (2) the impersonal-based mechanism which relates common identity attachment to VCCBC and subjective wellbeing. In order to understand the two proposed mechanisms, the research model was tested with data collected from members of a VC

Impact of Butterfly Wing-Pitch Interaction on Flight Performance

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P2

Chemical and acoustic directed processes for enhancing two-phase porous media fluid flow

This thesis presents a reservoir-on-a-chip study of waterflooding, acoustic streaming and ultrasonic streaming as enhanced oil recovery mechanism. Microfluidic devices with different porosities are fabricated using photolithography or close-packed microbeads to sever as reservoir-on-a-chip micromodels. Optical video fluorescence microscopy is used to track the invasion of a water phase through the oil saturated porous micromodel. In waterflooding study, the degree of water saturation is compared to water containing two different types of chemical modifiers, sodium dodecyl sulfate (SDS) and polyvinylpyrrolidone (PVP), with water in the absence of a surfactant used as a control. Image analysis of our video data yield saturation curves and calculate fractal dimension, which we use to identify how morphology changes the way as invading water phase moves through the porous media. An inverse analysis based on the implicit pressure explicit saturation (IMPES) simulation technique uses mobility ratio as an adjustable parameter to fit our experimental saturation curves. The results from our inverse analysis combined with our image analysis show that this platform can be used to evaluate the effectiveness of surfactants or polymers as additives for enhancing the transport of water through an oil-saturated porous medium. In acoustic streaming study, we also use microparticle image velocimetry to characterize acoustic streaming-induced pumping as a function of frequency and amplitude. A scaling model applied to the velocity distribution is used to construct a state diagram that connects acoustic pressure to filed frequency and amplitude. Based on the measurements of water phase displace oil saturated porous micromodel, we calculate the Black number as a function of frequency to show our system exhibits a narrow band dynamic response consistent with a system operating near resonance. Our observations are compared to a general model for Blake number as a function of frequency, porosity and voltage amplitude that was derived from a force balance model of micromodel undergoing force oscillation. In ultrasonic streaming study, we use particle tracking method to characterize diffusion coefficient and ultrasonic streaming induced as a function of frequency, voltage amplitude and porosity. Brownian dynamics model with ultrasonic streaming force and Hindered diffusion are used to simulation particle diffusion under two parallel wall microfluidic device when ultrasonic wave applies to the system. Based on these measurements, we observe that ultrasonic streaming phenomena appear significantly when amplitude voltage increase or porosity decrease. Besides, porous structure affect resonance frequency for the device. The results from this thesis are broadly applicable to systems beyond enhanced oil recovery, including separations, bio-analytical instrument, additive manufacturing, mixing and flow control

Trust-Building Mechanisms and Knowledge Sharing in Virtual Communities

Although trust has received much intention in the virtual communities (VCs) literature, few studies have been conducted to examine how trust develops in VCs. Drawing from prior literature on trust and knowledge sharing, a research model for understanding the antecedents of trust and the role of trust in VCs is presented. Data was collected from 324 members of a technical virtual community to test the model. The results help in identifying how the factors fall into three trust-building mechanisms build trust in the context VCs. The study discusses the theoretical and managerial implications of this study and proposes several future research directions

Application of the United States Soybean Export Council program's soy-optimized floating feeds and low volume, high density cage aquaculture technologies

The United States Soybean Export Council s (USSEC) Soy-In-Aquaculture (SIA) project in the Philippines introduced the Low Volume High Density (LVHD) cage culture production methodology in 2003. The aim of this technology is to maximize farmers profit, improve productivity, reduce feed conversion ratios (FCR) and limit environmental degradation. The Philippine fish farmers were very conservative and hesitant about adopting the USSEC SIA Low Volume High Density (LVHD) cage culture technology, particularly the new feeding techniques using extruded floating feeds. This conservative attitude was highlighted with different projects using Nile tilapia (Oreochromis niloticus), milkfish (Chanos chanos) and snubnose pompano (Trachinotus blochii) in USSEC SIA LVHD cage feeding demonstrations conducted in different commercial farms in the Philippines

Canopy Ecology of Swiss Needle Cast in Young and Mature/Old-growth Douglas-fir (Pseudotsuga menziesii)

Swiss needle cast (SNC) is a foliage disease of Douglas-fir caused by Nothophaeocryptopus gaeumannii, an Ascomycete fungus (Mycosphaerellaceae) that causes growth reductions in Douglas-fir plantations across the Pacific Northwest. Epidemiology of the fungus is generally well known in plantation trees, but the relationship between disease expression and foliage nutrition and some climate variables is unclear. While the dynamics of SNC in older trees is also poorly understood. In Chapter 2, data from the Swiss Needle Cast Cooperative (SNCC) research and monitoring plot network across western Oregon and SW Washington State was utilized to assess the associations between disease severity, needle retention, carbon, and 9 foliage nutrients (N, Na, K, P, Ca, Mg, Mn, Al, and S). Foliage samples were collected from upper, mid and lower crowns of five Douglas-firs from each plot. SNC disease severity was determined from 2-year old needles by multiplying the ratio of occluded stomates by the percentage of needles with fungal reproductive structures (pseudothecia) for the 50 needles. SNC disease severity and needle retention were more highly associated in the mid crown than in upper and lower crown. Mid-crown SNC disease severity and nutrient relationships were determined using linear mixed models. SNC disease severity showed statistically significant positive trends with C (p<0.001), N (p<0.001), Na (p<0.001), K (p=0.004), S (p<0.001), no relationship with Ca, Mg, or Al, and slightly negative trends that were not significant for P and Mn. Although some nutrients were associated with increasing SNC disease severity, more research is required to determine the cause-effect. In Chapter 3, climatic factors, which strongly influence epidemiology, intensification and impacts of disease on tree growth, are considered. Our study was conducted in 106 systematically placed research plots established by the Swiss Needle Cast Cooperative in 2013-2015. Climate variables tested were monthly and annual precipitation, minimum temperature, maximum temperature, mean temperature, mean dew point temperature, and maximum VPD. We also examined the influence of latitude and longitude on climate variables and severity of SNC. Minimum temperature and dew point temperature were the most significant factors related to SNC disease severity (p<0.001). Oct-Apr mean temperature, Oct-Apr maximum temperature, and Nov-Apr maximum VPD were also associated with SNC disease severity (p<0.001). Monthly precipitation was not associated with mean SNC disease severity during the summer months. Dew point temperature for all months was positively associated with SNC disease severity (p<0.001). We suggest that dew point temperature may be more important in epidemiology of N. gaeumannii than previously thought. Latitude had a strong relationship with SNC disease severity and climate variables, while longitude did not. Analyses of climate relationships within subregions in the study area indicated that relationships between SNC disease severity and climate variables were strongest in the Tillamook region of northwest Oregon. In Chapter 4, while there is considerable evidence of SNC disease in coastal Douglas-fir plantations, the severity of SNC in mature and old-growth forests is poorly understood. We compared the SNC severity, incidence, needle retention, and foliar nitrogen in tree crowns of mature and old-growth forests and nearby young forests at three locations in the Oregon Coast Range and four locations in the western Cascade Mountains of Oregon. Disease severity, as assessed on 2-year old needles, was greater in younger forests than older forests at all sites. Retention of 1-4 year-old needle cohorts did not differ between young and old trees, but older trees had much larger complements of >4 year-old needles. Incidence of disease was highest for 2-year-old needles in young trees and 3-5 year-old needles in older trees. Total foliar nitrogen concentration did not differ in needles of young and old trees, but at some locations total N differed between canopy positions. Leaf wetness differences were not consistent between young and old tree crowns and did not explain disease severity differences. However, at a study site in the core epidemic area, the younger stand had longer periods of wetness in the upper crowns than a nearby old stand. Leaf wetness and foliar N were hypothesized to play a role in SNC disease severity, but apparently these are not controlling factors. In younger stands, the fungus appeared to block stomates earlier than in older stands and stomatal occlusion was always greater on younger than older trees for 2 year old needles. We speculate that multiple factors may have caused the observed differences, including differences in thermal properties of older and younger stands, needle anatomy, chemical differences, or genetics of old tree and young trees. It is also possible that older trees are less impacted by SNC because they have experienced exposure to the disease over a longer period of time, and this influences host-fungus interactions. Also, four of the sites that we examined were outside the current epidemic area and were not considered diseased, so this may have influenced needle retention. The relationships observed in our study need testing with larger samples to determine if our results are generally applicable to Douglas-fir in western Oregon. From these studies, we tested nutrient and climate variables, which narrowed down the potential factors associated with SNC for further focused modeling. Also, we provided quantitative and qualitative description of SNC patterns comparing mature and young tress, and suggested more research about SNC in mature and old-growth Douglas-fir forests in needed because of the potential of SNC to influence stands of all ages

Breastmilk as a Multisensory Intervention for Relieving Pain During Newborn Screening Procedures: A Randomized Control Trial

[[abstract]]The study aim was to explore the effects of multisensory breastmilk interventions on short-term pain of infants during newborn screening. This is a randomized controlled trial. A total of 120 newborns were recruited and assigned by randomization to one of three treatment conditions: Condition 1 = routine care (gentle touch + verbal comfort); Condition 2 = breastmilk odor + routine care; or Condition 3 = breastmilk odor + taste + routine care. Pain was scored with the Neonatal Infant Pain Scale (NIPS). Data were collected from video recordings at 1 min intervals over the 11 phases of heel sticks: phase 1, 5 min before heel stick without stimuli (baseline); phase 2 to phase 6 (during heel stick); and phase 7 to phase 11 (recovery). Generalized estimating equations compared differences in pain scores for newborns over phases among the three conditions. Compared with the routine care, provision of the odor and taste of breastmilk reduce NIPS scores during heel sticks (B = −4.36, SE = 0.45, p < 0.001 [phase6 ]), and during recovery (B = −3.29, SE = 0.42, p < 0.001 [phase7]). Our findings provide new data, which supports the use of multisensory interventions that include breastmilk odor and taste in combination with gentle touch and verbal comfort to relieve pain in infants undergoing newborn screening.[[notice]]補正完

Nek5000/RS Performance on Advanced GPU Architectures

We demonstrate NekRS performance results on various advanced GPU architectures. NekRS is a GPU-accelerated version of Nek5000 that targets high performance on exascale platforms. It is being developed in DOE's Center of Efficient Exascale Discretizations, which is one of the co-design centers under the Exascale Computing Project. In this paper, we consider Frontier, Crusher, Spock, Polaris, Perlmutter, ThetaGPU, and Summit. Simulations are performed with 17x17 rod-bundle geometries from small modular reactor applications. We discuss strong-scaling performance and analysis.Comment: 24 pages, 13 figures, 2 table

Cost-Sensitive Learning for Recurrence Prediction of Breast Cancer

Breast cancer is one of the top cancer-death causes and specifically accounts for 10.4% of all cancer incidences among women. The prediction of breast cancer recurrence has been a challenging research problem for many researchers. Data mining techniques have recently received considerable attention, especially when used for the construction of prognosis models from survival data. However, existing data mining techniques may not be effective to handle censored data. Censored instances are often discarded when applying classification techniques to prognosis. In this paper, we propose a cost-sensitive learning approach to involve the censored data in prognostic assessment with better recurrence prediction capability. The proposed approach employs an outcome inference mechanism to infer the possible probabilistic outcome of each censored instance and adopt the cost-proportionate rejection sampling and a committee machine strategy to take into account these instances with probabilistic outcomes during the classification model learning process. We empirically evaluate the effectiveness of our proposed approach for breast cancer recurrence prediction and include a censored-data-discarding method (i.e., building the recurrence prediction model by only using uncensored data) and the Kaplan-Meier method (a common prognosis method) as performance benchmarks. Overall, our evaluation results suggest that the proposed approach outperforms its benchmark techniques, measured by precision, recall and F1 score