Improved Fan Control

Cooling large computer enclosures is an increasingly difficult task, usually requiring multiple fans and/or multiple rotors per fan. A technique is disclosed that reduces stress on a power distribution system for multiple fans by delaying individual fan control signals at the final distribution point near the fans

The influence of dyadic symptom distress on threat appraisals and self-efficacy in advanced cancer and caregiving

Physical and psychological symptoms experienced by patients with advanced cancer influence their wellbeing; how patient and family caregivers' symptom distress influence each other's wellbeing is less understood. This study examined the influence of patient and caregiver symptom distress on their threat appraisals and self-efficacy to cope with cancer

Meaning‐based coping, chronic conditions and quality of life in advanced cancer & caregiving

ObjectiveThis study examined the relationship between the number of co‐existing health problems (patient comorbidities and caregiver chronic conditions) and quality of life (QOL) among patients with advanced cancer and their caregivers and assessed the mediating and moderating role of meaning‐based coping on that relationship.MethodsData came from patients with advanced cancers (breast, colorectal, lung, and prostate) and their family caregivers (N = 484 dyads). Study hypotheses were examined with structural equation modeling using the actor‐partner interdependence mediation model. Bootstrapping and model constraints were used to test indirect effects suggested by the mediation models. An interaction term was added to the standard actor‐partner interdependence model to test for moderation effects.ResultsMore patient comorbidities were associated with lower patient QOL. More caregiver chronic conditions were associated with lower patient and caregiver QOL. Patient comorbidities and caregiver chronic conditions had a negative influence on caregiver meaning‐based coping but no significant influence on patient meaning based coping. Caregiver meaning‐based coping mediated relationships between patient comorbidities and caregiver health conditions and patient and caregiver QOL. No significant moderating effects were observed.ConclusionsDespite the severity of advanced cancer for patients and caregivers, the co‐existing health problems of one member of the dyad have the potential to directly or indirectly affect the wellbeing of the other. Future research should consider how the number of patient comorbidities and caregiver chronic conditions, as well as the ability of patients and caregivers to manage those conditions, influences their meaning‐based coping and wellbeing. Copyright © 2016 John Wiley & Sons, Ltd.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138410/1/pon4146_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138410/2/pon4146.pd

Mesh node communication system for fire figthers

This report describes the prototype and demonstration of a reliable local area network (LAN) of devices able to interconnect a crew of fire fighters with a communications node. The data consists of images for thermal cameras at a given rate and other low bandwith data taken from the different sensors of the fire fighter gear, that are connected to the transmitter using a Bluetooth personal area network (PAN). The physical environment is indoors and it is expected that all nodes of the communication networks are distributed in different positions into a building

From fat droplets to floating forests: cross-domain transfer learning using a PatchGAN-based segmentation model

Many scientific domains gather sufficient labels to train machine algorithms through human-in-the-loop techniques provided by the Zooniverse.org citizen science platform. As the range of projects, task types and data rates increase, acceleration of model training is of paramount concern to focus volunteer effort where most needed. The application of Transfer Learning (TL) between Zooniverse projects holds promise as a solution. However, understanding the effectiveness of TL approaches that pretrain on large-scale generic image sets vs. images with similar characteristics possibly from similar tasks is an open challenge. We apply a generative segmentation model on two Zooniverse project-based data sets: (1) to identify fat droplets in liver cells (FatChecker; FC) and (2) the identification of kelp beds in satellite images (Floating Forests; FF) through transfer learning from the first project. We compare and contrast its performance with a TL model based on the COCO image set, and subsequently with baseline counterparts. We find that both the FC and COCO TL models perform better than the baseline cases when using >75% of the original training sample size. The COCO-based TL model generally performs better than the FC-based one, likely due to its generalized features. Our investigations provide important insights into usage of TL approaches on multi-domain data hosted across different Zooniverse projects, enabling future projects to accelerate task completion.Comment: 5 pages, 4 figures, accepted for publication at the Proceedings of the ACM/CIKM 2022 (Human-in-the-loop Data Curation Workshop

The Bits of Silence : Redundant Traffic in VoIP

Human conversation is characterized by brief pauses and so-called turn-taking behavior between the speakers. In the context of VoIP, this means that there are frequent periods where the microphone captures only background noise – or even silence whenever the microphone is muted. The bits transmitted from such silence periods introduce overhead in terms of data usage, energy consumption, and network infrastructure costs. In this paper, we contribute by shedding light on these costs for VoIP applications. We systematically measure the performance of six popular mobile VoIP applications with controlled human conversation and acoustic setup. Our analysis demonstrates that significant savings can indeed be achievable - with the best performing silence suppression technique being effective on 75% of silent pauses in the conversation in a quiet place. This results in 2-5 times data savings, and 50-90% lower energy consumption compared to the next better alternative. Even then, the effectiveness of silence suppression can be sensitive to the amount of background noise, underlying speech codec, and the device being used. The codec characteristics and performance do not depend on the network type. However, silence suppression makes VoIP traffic network friendly as much as VoLTE traffic. Our results provide new insights into VoIP performance and offer a motivation for further enhancements, such as performance-aware codec selection, that can significantly benefit a wide variety of voice assisted applications, as such intelligent home assistants and other speech codec enabled IoT devices.Peer reviewe

Partial inhibition of mitochondrial complex I ameliorates Alzheimer\u27s disease pathology and cognition in APP/PS1 female mice.

Alzheimer\u27s Disease (AD) is a devastating neurodegenerative disorder without a cure. Here we show that mitochondrial respiratory chain complex I is an important small molecule druggable target in AD. Partial inhibition of complex I triggers the AMP-activated protein kinase-dependent signaling network leading to neuroprotection in symptomatic APP/PS1 female mice, a translational model of AD. Treatment of symptomatic APP/PS1 mice with complex I inhibitor improved energy homeostasis, synaptic activity, long-term potentiation, dendritic spine maturation, cognitive function and proteostasis, and reduced oxidative stress and inflammation in brain and periphery, ultimately blocking the ongoing neurodegeneration. Therapeutic efficacy in vivo was monitored using translational biomarkers FDG-PET, 31P NMR, and metabolomics. Cross-validation of the mouse and the human transcriptomic data from the NIH Accelerating Medicines Partnership-AD database demonstrated that pathways improved by the treatment in APP/PS1 mice, including the immune system response and neurotransmission, represent mechanisms essential for therapeutic efficacy in AD patients

Designing a multifaceted quality improvement intervention in primary care in a country where general practice is seeking recognition: the case of Cyprus

<p>Abstract</p> <p>Background</p> <p>Quality Improvement Interventions require significant financial investments, and therefore demand careful consideration in their design in order to maximize potential benefits. In this correspondence we present the methodological approach of a multifaceted quality improvement intervention aiming to improve quality of care in primary care, properly tailored for a country such as Cyprus where general practice is currently seeking recognition.</p> <p>Methods</p> <p>Our methodological approach was focused on the design of an open label, community-based intervention controlled trial using all patients from two urban and two rural public primary care centers diagnosed with hypertension and type II diabetes mellitus. The design of our intervention was grounded on a strong theoretical framework that included the Unified Theory of Acceptance and Use of Technology, and the Chronic Care Model, which synthesize evidence-based system changes in accordance with the Theory of Planned Behavior and the Theory of Reasoned Action. The primary outcome measure was improvement in the quality of care for two chronic diseases evaluated through specific clinical indicators, as well as the patient satisfaction assessed by the EUROPEP questionnaire and additional personal interviews.</p> <p>Results</p> <p>We designed a multifaceted quality improvement intervention model, supported by a varying degree of scientific evidence, tailored to local needs and specific country characteristics. Overall, the main components of the intervention were the development and adoption of an electronic medical record and the introduction of clinical guidelines for the management of the targeted chronic diseases facilitated by the necessary model of organizational changes.</p> <p>Conclusion</p> <p>Health planners and policy makers need to be aware of the potential use of certain theoretical models and applied methodology as well as inexpensive tools that may be suitably tailored to the local needs, in order to effectively design quality improvement interventions in primary care settings.</p

Defects in Mitochondrial Dynamics and Metabolomic Signatures of Evolving Energetic Stress in Mouse Models of Familial Alzheimer's Disease

The identification of early mechanisms underlying Alzheimer's Disease (AD) and associated biomarkers could advance development of new therapies and improve monitoring and predicting of AD progression. Mitochondrial dysfunction has been suggested to underlie AD pathophysiology, however, no comprehensive study exists that evaluates the effect of different familial AD (FAD) mutations on mitochondrial function, dynamics, and brain energetics.We characterized early mitochondrial dysfunction and metabolomic signatures of energetic stress in three commonly used transgenic mouse models of FAD. Assessment of mitochondrial motility, distribution, dynamics, morphology, and metabolomic profiling revealed the specific effect of each FAD mutation on the development of mitochondrial stress and dysfunction. Inhibition of mitochondrial trafficking was characteristic for embryonic neurons from mice expressing mutant human presenilin 1, PS1(M146L) and the double mutation of human amyloid precursor protein APP(Tg2576) and PS1(M146L) contributing to the increased susceptibility of neurons to excitotoxic cell death. Significant changes in mitochondrial morphology were detected in APP and APP/PS1 mice. All three FAD models demonstrated a loss of the integrity of synaptic mitochondria and energy production. Metabolomic profiling revealed mutation-specific changes in the levels of metabolites reflecting altered energy metabolism and mitochondrial dysfunction in brains of FAD mice. Metabolic biomarkers adequately reflected gender differences similar to that reported for AD patients and correlated well with the biomarkers currently used for diagnosis in humans.Mutation-specific alterations in mitochondrial dynamics, morphology and function in FAD mice occurred prior to the onset of memory and neurological phenotype and before the formation of amyloid deposits. Metabolomic signatures of mitochondrial stress and altered energy metabolism indicated alterations in nucleotide, Krebs cycle, energy transfer, carbohydrate, neurotransmitter, and amino acid metabolic pathways. Mitochondrial dysfunction, therefore, is an underlying event in AD progression, and FAD mouse models provide valuable tools to study early molecular mechanisms implicated in AD