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Growth charts are among the tools used by nutritionists to track infant and child well-being. Numerous countries have depicted growth charts on their postage stamps, along with other GOBI components of child health (oral rehydration, breastfeeding, and immunizations). Postage stamps are useful in conveying essential health information to the populace and they honor worldwide efforts to improve child health. This article presents examples of GOBI depictions on postage stamps around the world, with special focus on growth charts.

The question addressed in this paper is whether cotton textiles mercerized with liquid ammonia (L-NH3) can be distinguished from NaOH mercerized cotton textiles with FTIR-ATR spectroscopy. In collaboration with a process-house, cotton textiles were treated with L-NH3, NaOH, neither or both. The treatment conditions were set to mimic commercial-scale operations. The samples were then analyzed with FTIR-ATR spectroscopy, and for comparison, also with powder X-ray diffraction. The analyses were aimed at detecting changes in the cellulose crystal lattice structure that result from the two mercerization processes. The measured spectra and diffractograms were evaluated both visually and with Principal Component Analysis (PCA), and the results show that with FTIR-ATR spectroscopy it was possible to differentiate between the untreated, L-NH3 mercerized and NaOH mercerized textiles, whereas with X-ray diffraction it was difficult to detect differences between the untreated and treated samples. The better performance of FTIR-ATR spectroscopy is attributed to the method being more sensitive to changes on sample surfaces, whereas X-ray diffraction results are more representative of the sample bulk. The samples were treated under conditions mimicking commercial-scale operations, which are optimized to maximize treatment speed. Hence, the mercerization induced changes are likely to be limited to sample surfaces and hence detectable with FTIR-ATR spectroscopy but not with X-ray diffraction. It is reported that Sum Frequency Generation Vibrational Spectroscopy, another surface-limited analytical method, may also be employed for detection of mercerization type, but FTIR-ATR spectroscopy has the advantages of ease of operation and the devices are less expensive.

Despite the suppression of human immunodeficiency virus (HIV) replication by combined antiretroviral therapy (cART), 50–60% of HIV-infected patients suffer from HIV-associated neurocognitive disorders (HAND). Studies are uncovering the role of extracellular vesicles (EVs), especially exosomes, in the central nervous system (CNS) due to HIV infection. We investigated links among circulating plasma exosomal (crExo) proteins and neuropathogenesis in simian/human immunodeficiency virus (SHIV)-infected rhesus macaques (RM) and HIV-infected and cART treated patients (Patient-Exo). Isolated EVs from SHIV-infected (SHIV-Exo) and uninfected (CTL-Exo) RM were predominantly exosomes (particle size < 150 nm). Proteomic analysis quantified 5654 proteins, of which 236 proteins (~4%) were significantly, differentially expressed (DE) between SHIV-/CTL-Exo. Interestingly, different CNS cell specific markers were abundantly expressed in crExo. Proteins involved in latent viral reactivation, neuroinflammation, neuropathology-associated interactive as well as signaling molecules were expressed at significantly higher levels in SHIV-Exo than CTL-Exo. However, proteins involved in mitochondrial biogenesis, ATP production, autophagy, endocytosis, exocytosis, and cytoskeleton organization were significantly less expressed in SHIV-Exo than CTL-Exo. Interestingly, proteins involved in oxidative stress, mitochondrial biogenesis, ATP production, and autophagy were significantly downregulated in primary human brain microvascular endothelial cells exposed with HIV+/cART+ Patient-Exo. We showed that Patient-Exo significantly increased blood–brain barrier permeability, possibly due to loss of platelet endothelial cell adhesion molecule-1 protein and actin cytoskeleton structure. Our novel findings suggest that circulating exosomal proteins expressed CNS cell markers—possibly associated with viral reactivation and neuropathogenesis—that may elucidate the etiology of HAND.

Frost accumulation is a common but undesired phenomenon for air-source heat pump (ASHP) systems in winter operations. Reverse-cycle defrosting that applies heat to the outdoor coil by reversing the thermodynamic cycle, is one of the predominant means for periodic removal of the accumulated frost. This paper presents a dynamic modeling framework for ASHPs under cycling of frosting and reverse-cycle defrosting operations. A uniform model structure was applied to frost formation and melting models, which were incorporated into the evaporator model, without a need for reinitializing the system when the operating mode switches between heating and defrosting. The developed model was simulated to predict transients of a residential ASHP under multiple cycles of frosting and defrosting operations, and results yielded good agreement with measurements.

A load-based testing methodology has recently been developed for laboratory testing of residential cooling equipment with its integrated controls that employs a model to emulate building dynamics and their interaction with equipment controls. This approach is part of a new performance rating standard that utilizes a bin method to estimate a seasonal energy efficiency (CSA EXP-07, 2019; Cheng et al., 2021). However, a “holy grail” for future equipment performance rating is to be able to map equipment performance using load-based testing results and then implement the map as a "model" in building energy simulations to generate seasonal performance ratings that are specific to various building and climate types. With this goal in mind, this paper presents a performance mapping methodology that incorporates a “gray-box” model structure that uses inputs that are consistent with building energy simulation programs (sensible cooling load and equipment inlet conditions) and outputs key performance metrics (total sensible and latent cooling rates, power consumption, and COP). A strategy and a test matrix for training the model with a relatively small number of testing points were established by developing a successive optimization approach to identify the best 12 test conditions to apply for training from a larger set of available data. In order to develop, demonstrate, and validate the modeling and training approach, load-based laboratory testing was set up within psychrometric chambers and testing was performed to generate 39 quasi-steady-state data points over a range of loads and boundary conditions with a test unit operating with its normal integrated controls. The best model trained using the optimal training subset of 12 data points was able to represent the equipment performance across the operating envelope within ± 10 % .

A computationally efficient but accurate dynamic modeling approach for vapor compression systems is important for many applications. Nonlinear model order reduction techniques which generate reduced order models based on high fidelity vapor compression cycle (VCC) models are attractive for the purposes. In this paper, a number of technical challenges of applying model order reduction methods to VCCs are described and corresponding solution approaches are presented. It starts with a reformulation of a standard finite volume heat exchanger model for matching the baseline model reduction structure. Reduced order models for evaporator and condenser are constructed from numerical snapshots of the high fidelity models using Proper Orthogonal Decomposition (POD). Methodologies for system stability and numerical efficiency of POD reduced order models are described. The reduced order heat exchanger models are then coupled with quasi-static models of other components to form a reduced order cycle model. Transient simulations were conducted over a wide range of operating conditions and results were compared with the full order model as well as measurements. The validation results indicate that the reduced order model can execute much faster than a high-fidelity finite volume model with negligible prediction errors.

Two bipyridine isomers (2,2′- and 4,4′-), used as coformers and ligands in coordination chemistry, were subjected to solid form screening and crystal structure prediction. One anhydrate and a formic acid disolvate were crystallized for 2,2′-bipyridine, whereas multiple solid-state forms, anhydrate, dihydrate, and eight solvates with carboxylic acids, including a polymorphic acetic acid disolvate, were found for the 4,4′-isomer. Seven of the solvates are reported for the first time, and structural information is provided for six of the new solvates. All twelve solid-state forms were investigated comprehensively using experimental [thermal analysis, isothermal calorimetry, X-ray diffraction, gravimetric moisture (de)sorption, and IR spectroscopy] and computational approaches. Lattice and interaction energy calculations confirmed the thermodynamic driving force for disolvate formation, mediated by the absence of H-bond donor groups of the host molecules. The exposed location of the N atoms in 4,4′-bipyridine facilitates the accommodation of bigger carboxylic acids and leads to higher conformational flexibility compared to 2,2′-bipyridine. For the 4,4′-bipyridine anhydrate ↔ hydrate interconversion hardly any hysteresis and a fast transformation kinetics are observed, with the critical relative humidity being at 35% at room temperature. The computed anhydrate crystal energy landscapes have the 2,2′-bipyridine as the lowest energy structure and the 4,4′-bipyridine among the low-energy structures and suggest a different crystallization behavior of the two compounds., The solid form landscapes of 2,2′- and 4,4′-bipyridine were explored experimentally and computationally. The position of the nitrogen atoms defines not only the conformational flexibility of the molecule but also the crystallization behavior. 4.4′-Bipyridine was found to be more prone to solvate (including hydrate) formation than its 2,2′-isomer.

Children's ability to recognize object shape is foundational for successful early word learning. However, the prototypical shape of objects may not be easily accessible-take margarita glasses, for instance. The current study examined 304 U.S. children 17- to 42-month-old (152 females) from 2017 to 2020, asking how shape, age, and vocabulary abilities predict recognition of everyday objects. Children's ability to recognize objects increases with age and vocabulary, replicating prior work. Moreover, performance was partially moderated by object's typicality and shape features, and children's own attention to shape (shape bias) may mediate the effect, especially with prototypically shaped objects. The current study highlights how both child-specific variables and context features interact to shape language abilities, underscoring the emergent and multi-causal nature of word learning.

As one of the top public health challenges outlined by the Centers for Disease Control (CDC), estimates report that hospital acquired infections (HAIs) claim the lives of 99,000 Americans and cost healthcare providers over $28 billion each year. In addition to underlying conditions related to age, elderly patients in long-term care facilities are at an elevated risk of acquiring HAIs. A large percentage of HAIs is attributable to contaminated surfaces and medical devices. To that end, this study utilized a metatranscriptomic sequencing workflow (CSI-Dx™) to profile active microbial communities from surfaces in the HJ Heinz Community Living Center, a long-term care facility in the Veterans Affairs Pittsburgh Health Care System. Swabs were collected from high-touch surfaces (Keyboard, Ledge, Workstation on Wheels, Worksurfaces) before (Baseline) and after cleanSURFACES® were installed at 4 timepoints (Day 1, Day 7, Day 14, and Day 30). Microbial richness was significantly reduced after cleanSURFACES® intervention (Wilcoxon test with Holm correction, p=0.000179). Beta diversity results revealed distinct clustering between Baseline and Post-intervention samples (Adonis, pStaphylococcus aureus, Staphylococcus epidermidis, Staphylococcus hominis) and fungal (Malassezia restricta, Candida albicans, Candida glabrata, and Candida orthopsilosis) expression of opportunistic pathogens was observed. Additionally, a subset of taxa (Corynebacterium, Cutibacterium acnes, and Ralstonia pickettii) was present in specific Post-intervention timepoints and surface types. This study revealed decreased microbial activity, highlighting the potential for the combinatorial application of cleanSURFACES® and regular decontamination practices to reduce the prevalence of microbes causing HAIs.

In this paper, we introduce a real-time modelling approach to predict the heating and cooling energy consumption of each housing unit in multi-family residential buildings. We first present measure...