Building Energy Modeling for Green Architecture and Intelligent Dashboard Applications

Buildings are responsible for 40% of the carbon emissions in the United States. Energy efficiency in this sector is key to reducing overall greenhouse gas emissions. This work studied the passive technique called the roof solar chimney for reducing the cooling load in homes architecturally. Three models of the chimney were created: a zonal building energy model, computational fluid dynamics model, and numerical analytic model. The study estimated the error introduced to the building energy model (BEM) through key assumptions, and then used a sensitivity analysis to examine the impact on the model outputs. The conclusion was that the error in the building energy model is small enough to use it for building simulation reliably. Further studies simulated the roof solar chimney in a whole building, integrated into one side of the roof. Comparisons were made between high and low efficiency constructions, and three ventilation strategies. The results showed that in four US climates, the roof solar chimney results in significant cooling load energy savings of up to 90%. After developing this new method for the small scale representation of a passive architecture technique in BEM, the study expanded the scope to address a fundamental issue in modeling - the implementation of the uncertainty from and improvement of occupant behavior. This is believed to be one of the weakest links in both accurate modeling and proper, energy efficient building operation. A calibrated model of the Mascaro Center for Sustainable Innovation’s LEED Gold, 3,400 m2 building was created. Then algorithms were developed for integration to the building’s dashboard application that show the occupant the energy savings for a variety of behaviors in real time. An approach using neural networks to act on real-time building automation system data was found to be the most accurate and efficient way to predict the current energy savings for each scenario. A stochastic study examined the impact of the representation of unpredictable occupancy patterns on model results. Combined, these studies inform modelers and researchers on frameworks for simulating holistically designed architecture and improving the interaction between models and building occupants, in residential and commercial settings

Automated CO2 and CH4 monitoring system for continuous estimation of degassing related to hydropower

Reliable measurement of greenhouse gas emissions from reservoirs is essential for estimating the carbon footprint of the hydropower industry. Among the different emission pathways, degassing downstream of the turbines and spillway is poorly documented mainly because of the safety stakes related to sampling up and downstream the power plants. The alternative being to sample the water from the turbine inside the station, this study aimed to assemble a custom automated CO2 and CH4 monitoring system (SAGES), especially designed for long-term surveys in hydropower facilities, with a special focus on low maintenance requirements. The SAGES combines infrared and laser technologies with a modular programming approach and run with a specifically designed plexiglass equilibration system (PES) that maintain a permanent headspace and avoid clogging by suspended solids. Although the SAGES is based on commercially available devices, it is the first time they are combined and used with the gas equilibrator. To ensure the reliability of the mounting and to control the quality of the readings, the system was tested in laboratory prior to its installation in generating stations. SAGES and PES performances were compared with those of generic devices available on the market although less adapted to the specific deployments targeted. The SAGES gas partial pressure measurements were accurate and linear in the entire range tested: 0 to 5,000 ppm for pCO2 and 0 to 600 and 10,000 ppm for pCH4. Gas PP measurements were comparable to the reference CO2/CH4 sensor and there was no drift during long term deployment. The SAGES/PES installed in 2021 in cascading generating stations of the Romaine complex collected more than 28,000 data points over a 10-month period and required only two maintenances. Results show that the SAGES is a reliable tool that provide long-term CO2 and CH4 dataset in generating stations while requiring minimal energy, care and maintenance. The data collected in turbine water and the recent use of the SAGES in peat land by a collaborative team demonstrate how the SAGES systems can efficiently contribute to the understanding of reservoir carbon cycles

Hysteresis in mesoscopic superconducting disks: the Bean-Livingston barrier

The magnetization behavior of mesoscopic superconducting disks can show hysteretic behavior which we explain by using the Ginzburg-Landau (GL) theory and properly taking into account the de-magnetization effects due to geometrical form factors. In large disks the Bean-Livingston surface barrier is responsible for the hysteresis. While in small disks a volume barrier is responsible for this hysteresis. It is shown that although the sample magnetization is diamagnetic (negative), the measured magnetization can be positive at certain fields as observed experimentally, which is a consequence of the de-magnetization effects and the experimental set up.Comment: Latex file, 4 ps file

Metrics with Prescribed Ricci Curvature near the Boundary of a Manifold

Suppose $M$ is a manifold with boundary. Choose a point $o\in\partial M$. We investigate the prescribed Ricci curvature equation \Ric(G)=T in a neighborhood of $o$ under natural boundary conditions. The unknown $G$ here is a Riemannian metric. The letter $T$ in the right-hand side denotes a (0,2)-tensor. Our main theorems address the questions of the existence and the uniqueness of solutions. We explain, among other things, how these theorems may be used to study rotationally symmetric metrics near the boundary of a solid torus $\mathcal T$. The paper concludes with a brief discussion of the Einstein equation on $\mathcal T$.Comment: 13 page

The effects of parasitism and body length on positioning within wild fish shoals

The influence of body length and parasitism on the positioning behaviour of individuals in wild fish shoals was investigated by a novel means of capturing entire shoals of the banded killifish (Fundulus diaphanus, Lesueur) using a grid-net that maintained the two-dimensional positions of individuals within shoals. Fish in the front section of a shoal were larger than those in the rear. Individuals parasitized by the digenean trematode (Crassiphiala bulboglossa, Haitsma) showed a tendency to occupy the front of shoals. Parasitized fish were also found more in peripheral positions than central ones in a significant number of shoals. Shoal geometry was affected by the overall parasite prevalence of shoal members; shoals with high parasite prevalence displayed increasingly phallanx-like shoal formations, whereas shoals with low prevalence were more elliptical. There was no relationship between body length and parasite abundance or prevalence in the fish population which suggests body length and parasite status are independent predictors of positioning behaviour. Solitary individuals found outside shoals were both more likely to be parasitized and had higher parasite abundance than individuals engaged in shoaling. Differences in the shoaling behaviour of parasitized and unparasitized fish are discussed in the context of the adaptive manipulation hypothesis

Telehealth and Mobile Health Applied To IntegratedBehavioral Care: OpportunitiesFor Progress In New Hampshire

This paper is an accompanying document to a webinar delivered on May 16, 2017, for the New Hampshire Citizens Health Initiative (Initiative). As integrated behavioral health efforts in New Hampshire gain traction, clinicians, administrators, payers, and policy makers are looking for additional efficiencies in delivering high quality healthcare. Telehealth and mobile health (mHealth) have the opportunity to help achieve this while delivering a robust, empowered patient experience. The promise of video-based technology was first made in 1964 as Bell Telephone shared its Picturephone® with the world. This was the first device with audio and video delivered in an integrated technology platform. Fast-forward to today with Skype, FaceTime, and webinar tools being ubiquitous in our personal and business lives, but often slow to be adopted in the delivery of medicine. Combining technology-savvy consumers with New Hampshire’s high rate of electronic health record (EHR) technology adoption, a fairly robust telecommunications infrastructure, and a predominately rural setting, there is strong foundation for telehealth and mHealth expansion in New Hampshire’s integrated health continuum

Integrating Behavioral Health & Primary Care in New Hampshire: A Path Forward to Sustainable Practice & Payment Transformation

New Hampshire residents face challenges with behavioral and physical health conditions and the interplay between them. National studies show the costs and the burden of illness from behavioral health conditions and co-occurring chronic health conditions that are not adequately treated in either primary care or behavioral health settings. Bringing primary health and behavioral health care together in integrated care settings can improve outcomes for both behavioral and physical health conditions. Primary care integrated behavioral health works in conjunction with specialty behavioral health providers, expanding capacity, improving access, and jointly managing the care of patients with higher levels of acuity In its work to improve the health of NH residents and create effective and cost-effective systems of care, the NH Citizens Health Initiative (Initiative) created the NH Behavioral Health Integration Learning Collaborative (BHI Learning Collaborative) in November of 2015, as a project of its Accountable Care Learning Network (NHACLN). Bringing together more than 60 organizations, including providers of all types and sizes, all of the state’s community mental health centers, all of the major private and public insurers, and government and other stakeholders, the BHI Learning Collaborative built on earlier work of a NHACLN Workgroup focused on improving care for depression and co-occurring chronic illness. The BHI Learning Collaborative design is based on the core NHACLN philosophy of “shared data and shared learning” and the importance of transparency and open conversation across all stakeholder groups. The first year of the BHI Learning Collaborative programming included shared learning on evidence-based practice for integrated behavioral health in primary care, shared data from the NH Comprehensive Healthcare Information System (NHCHIS), and work to develop sustainable payment models to replace inadequate Fee-for-Service (FFS) revenues. Provider members joined either a Project Implementation Track working on quality improvement projects to improve their levels of integration or a Listen and Learn Track for those just learning about Behavioral Health Integration (BHI). Providers in the Project Implementation Track completed a self-assessment of levels of BHI in their practice settings and committed to submit EHR-based clinical process and outcomes data to track performance on specified measures. All providers received access to unblinded NHACLN Primary Care and Behavioral Health attributed claims data from the NHCHIS for provider organizations in the NH BHI Learning Collaborative. Following up on prior work focused on developing a sustainable model for integrating care for depression and co-occurring chronic illness in primary care settings, the BHI Learning Collaborative engaged consulting experts and participants in understanding challenges in Health Information Technology and Exchange (HIT/HIE), privacy and confidentiality, and workforce adequacy. The BHI Learning Collaborative identified a sustainable payment model for integrated care of depression in primary care. In the process of vetting the payment model, the BHI Learning Collaborative also identified and explored challenges in payment for Substance Use Disorder Screening, Brief Intervention and Referral to Treatment (SBIRT). New Hampshire’s residents will benefit from a health care system where primary care and behavioral health are integrated to support the care of the whole person. New Hampshire’s current opiate epidemic accentuates the need for better screening for behavioral health issues, prevention, and treatment referral integrated into primary care. New Hampshire providers and payers are poised to move towards greater integration of behavioral health and primary care and the Initiative looks forward to continuing to support progress in supporting a path to sustainable integrated behavioral and primary care

Depressive Symptomology Predicts Nighttime Central Systolic Blood Pressure Dipping in Adults

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MiR-137 Targets Estrogen-Related Receptor Alpha and Impairs the Proliferative and Migratory Capacity of Breast Cancer Cells

ERRα is an orphan nuclear receptor emerging as a novel biomarker of breast cancer. Over-expression of ERRα in breast tumor is considered as a prognostic factor of poor clinical outcome. The mechanisms underlying the dysexpression of this nuclear receptor, however, are poorly understood. MicroRNAs (miRNAs) regulate gene expression at the post-transcriptional level and play important roles in tumor initiation and progression. In the present study, we have identified that the expression of ERRα is regulated by miR-137, a potential tumor suppressor microRNA. The bioinformatics search revealed two putative and highly conserved target-sites for miR-137 located within the ERRα 3′UTR at nt 480–486 and nt 596–602 respectively. Luciferase-reporter assay demonstrated that the two predicted target sites were authentically functional. They mediated the repression of reporter gene expression induced by miR-137 in an additive manner. Moreover, ectopic expression of miR-137 down-regulated ERRα expression at both protein level and mRNA level, and the miR-137 induced ERRα-knockdown contributed to the impaired proliferative and migratory capacity of breast cancer cells. Furthermore, transfection with miR-137mimics suppressed at least two downstream target genes of ERRα–CCNE1 and WNT11, which are important effectors of ERRα implicated in tumor proliferation and migration. Taken together, our results establish a role of miR-137 in negatively regulating ERRα expression and breast cancer cell proliferation and migration. They suggest that manipulating the expression level of ERRα by microRNAs has the potential to influence breast cancer progression

Mammary molecular portraits reveal lineage-specific features and progenitor cell vulnerabilities.

The mammary epithelium depends on specific lineages and their stem and progenitor function to accommodate hormone-triggered physiological demands in the adult female. Perturbations of these lineages underpin breast cancer risk, yet our understanding of normal mammary cell composition is incomplete. Here, we build a multimodal resource for the adult gland through comprehensive profiling of primary cell epigenomes, transcriptomes, and proteomes. We define systems-level relationships between chromatin-DNA-RNA-protein states, identify lineage-specific DNA methylation of transcription factor binding sites, and pinpoint proteins underlying progesterone responsiveness. Comparative proteomics of estrogen and progesterone receptor-positive and -negative cell populations, extensive target validation, and drug testing lead to discovery of stem and progenitor cell vulnerabilities. Top epigenetic drugs exert cytostatic effects; prevent adult mammary cell expansion, clonogenicity, and mammopoiesis; and deplete stem cell frequency. Select drugs also abrogate human breast progenitor cell activity in normal and high-risk patient samples. This integrative computational and functional study provides fundamental insight into mammary lineage and stem cell biology