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To investigate the link between sleep disruption and cognitive impairment in childhood epilepsy by studying the effect of epilepsy on sleep homeostasis, as reflected in slow-wave activity (SWA).We examined SWA from overnight EEG-polysomnography in 19 children with focal epilepsy (mean [SD] age 11 years 6 months [3 years], range 6 years 6 months-15 years 6 months; 6 females, 13 males) and 18 age- and sex-matched typically developing controls, correlating this with contemporaneous memory consolidation task scores, full-scale IQ, seizures, and focal interictal discharges.Children with epilepsy did not differ significantly from controls in overnight SWA decline (p = 0.12) or gain in memory performance with sleep (p = 0.27). SWA was lower in patients compared to controls in the first hour of non-rapid eye movement sleep (p = 0.021), although not in those who remained seizure-free (p = 0.26). Full-scale IQ did not correlate with measures of SWA in patients or controls. There was no significant difference in SWA measures between focal and non-focal electrodes.Overnight SWA decline is conserved in children with focal epilepsy and may underpin the preservation of sleep-related memory consolidation in this patient group. Reduced early-night SWA may reflect impaired or immature sleep homeostasis in those with a higher seizure burden.

Sperm cells are transcriptionally and translationally silent. Therefore, they may use one of the remaining mechanisms to respond to stimuli in their environment, the post-translational modification of their proteins. Here we examined three post-translational modifications, acetylation, glutamylation, and glycylation of the protein tubulin in human and cattle sperm. Tubulin is the monomer that makes up microtubules, and microtubules constitute the core component of both the sperm centrioles and the axoneme. We found that the sperm of both species were labeled by antibodies against acetylated tubulin and glutamylated tubulin.

Background Increased understanding of whether individuals who have recovered from COVID-19 are protected from future SARS-CoV-2 infection is an urgent requirement. We aimed to investigate whether antibodies against SARS-CoV-2 were associated with a decreased risk of symptomatic and asymptomatic reinfection. Methods A large, multicentre, prospective cohort study was done, with participants recruited from publicly funded hospitals in all regions of England. All health-care workers, support staff, and administrative staff working at hospitals who could remain engaged in follow-up for 12 months were eligible to join The SARS-CoV-2 Immunity and Reinfection Evaluation study. Participants were excluded if they had no PCR tests after enrolment, enrolled after Dec 31, 2020, or had insufficient PCR and antibody data for cohort assignment. Participants attended regular SARS-CoV-2 PCR and antibody testing (every 2–4 weeks) and completed questionnaires every 2 weeks on symptoms and exposures. At enrolment, participants were assigned to either the positive cohort (antibody positive, or previous positive PCR or antibody test) or negative cohort (antibody negative, no previous positive PCR or antibody test). The primary outcome was a reinfection in the positive cohort or a primary infection in the negative cohort, determined by PCR tests. Potential reinfections were clinically reviewed and classified according to case definitions (confirmed, probable, or possible) and symptom-status, depending on the hierarchy of evidence. Primary infections in the negative cohort were defined as a first positive PCR test and seroconversions were excluded when not associated with a positive PCR test. A proportional hazards frailty model using a Poisson distribution was used to estimate incidence rate ratios (IRR) to compare infection rates in the two cohorts. Findings From June 18, 2020, to Dec 31, 2020, 30 625 participants were enrolled into the study. 51 participants withdrew from the study, 4913 were excluded, and 25 661 participants (with linked data on antibody and PCR testing) were included in the analysis. Data were extracted from all sources on Feb 5, 2021, and include data up to and including Jan 11, 2021. 155 infections were detected in the baseline positive cohort of 8278 participants, collectively contributing 2 047 113 person-days of follow-up. This compares with 1704 new PCR positive infections in the negative cohort of 17 383 participants, contributing 2 971 436 person-days of follow-up. The incidence density was 7·6 reinfections per 100 000 person-days in the positive cohort, compared with 57·3 primary infections per 100 000 person-days in the negative cohort, between June, 2020, and January, 2021. The adjusted IRR was 0·159 for all reinfections (95% CI 0·13–0·19) compared with PCR-confirmed primary infections. The median interval between primary infection and reinfection was more than 200 days. Interpretation A previous history of SARS-CoV-2 infection was associated with an 84% lower risk of infection, with median protective effect observed 7 months following primary infection. This time period is the minimum probable effect because seroconversions were not included. This study shows that previous infection with SARS-CoV-2 induces effective immunity to future infections in most individuals. Funding Department of Health and Social Care of the UK Government, Public Health England, The National Institute for Health Research, with contributions from the Scottish, Welsh and Northern Irish governments.

Metal-organic frameworks (MOFs) are a class of crystalline materials composed of metal nodes or clusters connected via semi-rigid organic linkers. Owing to their high surface area, porosity, and tunability, MOFs have received significant attention for numerous applications such as gas separation and storage. Atomistic simulations and data-driven methods (e.g., machine learning) have been successfully employed to screen large databases and successfully develop new experimentally synthesized and validated MOFs for CO2 capture. To enable data-driven materials discovery for any application, the first (and arguably most crucial) step is database curation. This work introduces the ab initio REPEAT charge MOF (ARC-MOF) database. This is a database of ~280,000 MOFs which have been either experimentally characterized or computationally generated, spanning all publicly available MOF databases. A key feature of ARC-MOF is that it contains DFT-derived electrostatic potential fitted partial atomic charges for each MOF. Additionally, ARC-MOF contains pre-computed descriptors for out-of-the-box machine learning applications. An in-depth analysis of the diversity of ARC-MOF with respect to the currently mapped design space of MOFs was performed – a critical, yet commonly overlooked aspect of previously reported MOF databases. Using this analysis, balanced subsets from ARC-MOF for various machine learning purposes have been identified. Other chemical and geometric diversity analyses are presented, with an analysis on the effect of charge assignment method on atomistic simulation of gas uptake in MOFs.

Soybean (Glycine max [L.] Merrill) yield losses as a result of plant diseases were estimated by university and government plant pathologists in 29 soybean producing states in the United States and in Ontario, Canada, from 2015 through 2019. In general, the estimated losses that resulted from each of 28 plant diseases or pathogens varied by state or province as well as year. Soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) caused more than twice as much loss as any other disease during the survey period. Seedling diseases (caused by various pathogens), Sclerotinia stem rot (white mold) (caused by Sclerotinia sclerotiorum [Lib.] de Bary), and sudden death syndrome (caused by Fusarium virguliforme O’Donnell & T. Aoki) caused the next greatest yield losses, in descending order. Following SCN, the most damaging diseases in the northern United States and Ontario differed from those in the southern United States. The estimated mean economic loss from all soybean diseases, averaged across the United States and Ontario, Canada was US$45 per acre (US$111 per hectare). The outcome from the current survey will provide pertinent information regarding the important soybean diseases and their overall severity in the soybean crop and help guide future research and Extension efforts on managing soybean diseases.

Metal–organic frameworks (MOFs) have garnered interest as potential solid sorbent materials for postcombustion CO2 capture. With a seemingly infinite design space, high-throughput computational scr...

BACKGROUND Identifying early stages of hypersensitivity pneumonitis (HP) is hampered by variable presentation, heterogeneous or undetected causal antigens and lack of gold-standard biomarkers. Krebs von den Lungen (KL)-6 is pathophysiological biomarker of alveolar epithelial damage. Pigeon fanciers, susceptible to HP, provide a model to investigate early HP. OBJECTIVE To test the hypothesis that plasma concentrations of KL-6 are increased in early-stage acute HP. METHODS Clinical history, spirometry and blood samples were obtained from pigeon fanciers, 20 with intermittent acute symptoms indicative of developing HP, 27 with no symptoms and 10 healthy subjects with no avian exposure. Plasma KL-6 (units/mL) and pigeon antigen-specific IgG antibody were quantified by enzyme immunoassay. Blood lymphocytes were quantified by flow cytometry and antigen specificity by in vitro cytokine production. RESULTS KL-6 was higher in fanciers than controls, median (IQR) 452 (244, 632) vs 274 (151, 377), P = .01. Although fanciers with symptoms had similar antigen exposure and lung function, they had higher KL-6 than those without, 632 (468, 1314) vs 320 (200, 480), P

Layer-by-layer microparticle (LbL-MP) fabrication was used to produce synthetic vaccines presenting a fusion peptide containing RSV G protein CX3C chemokine motif and a CD8 epitope of the RSV matrix protein 2 (GM2) with or without a covalently linked TLR2 agonist (Pam3.GM2). Immunization of BALB/c mice with either GM2 or Pam3.GM2 LbL-MP in the absence of adjuvant elicited G-specific antibody responses and M2-specific CD8+ T-cell responses. Following challenge with RSV, mice immunized with the GM2 LbL-MP vaccine developed a Th2-biased immune response in the lungs with elevated levels of IL-4, IL-5, IL-13, and eotaxin in the bronchoalveolar lavage (BAL) fluid and a pulmonary influx of eosinophils. By comparison, mice immunized with the Pam3.GM2 LbL-MP vaccine had considerably lower to non-detectable levels of the Th2 cytokines and chemokines and very low numbers of eosinophils in the BAL fluid post-RSV challenge. In addition, mice immunized with the Pam3.GM2 LbL-MP also had higher levels of RSV G-specific IgG2a and IgG2b in the post-challenge BAL fluid compared to those immunized with the GM2 LbL-MP vaccine. While both candidates protected mice from infection following challenge, as evidenced by the reduction or elimination of RSV plaques, the inclusion of the TLR2 agonist yielded a more potent antibody response, greater protection, and a clear shift away from Th2/eosinophil responses. Since the failure of formalin-inactivated RSV (FI-RSV) vaccines tested in the 1960s has been hypothesized to be partly due to the ablation of host TLR engagement by the vaccine and inappropriate Th2 responses upon subsequent viral infection, these findings stress the importance of appropriate engagement of the innate immune response during initial exposure to RSV G CX3C.

White adipose tissue (WAT), once regarded as morphologically and functionally bland, is now recognized to be dynamic, plastic, heterogenous, and involved in a wide array of biological processes including energy homeostasis, glucose and lipid handling, blood pressure control, and host defense1. High fat feeding and other metabolic stressors cause dramatic changes in adipose morphology, physiology, and cellular composition1, and alterations in adiposity are associated with insulin resistance, dyslipidemia, and type 2 diabetes (T2D)2. Here, we provide detailed cellular atlases of human and murine subcutaneous and visceral white fat at single cell resolution across a range of body weight. We identify subpopulations of adipocytes, adipose stem and progenitor cells (ASPCs), vascular, and immune cells and demonstrate commonalities and differences across species and dietary conditions. We link specific cell types to increased risk of metabolic disease, and we provide an initial blueprint for a comprehensive set of interactions between individual cell types in the adipose niche in leanness and obesity. These data comprise an extensive resource for the exploration of genes, traits, and cell types in the function of WAT across species, depots, and nutritional conditions.

Summary Background BNT162b2 mRNA and ChAdOx1 nCOV-19 adenoviral vector vaccines have been rapidly rolled out in the UK from December, 2020. We aimed to determine the factors associated with vaccine coverage for both vaccines and documented the vaccine effectiveness of the BNT162b2 mRNA vaccine in a cohort of health-care workers undergoing regular asymptomatic testing. Methods The SIREN study is a prospective cohort study among staff (aged ≥18 years) working in publicly-funded hospitals in the UK. Participants were assigned into either the positive cohort (antibody positive or history of infection [indicated by previous positivity of antibody or PCR tests]) or the negative cohort (antibody negative with no previous positive test) at the beginning of the follow-up period. Baseline risk factors were collected at enrolment, symptom status was collected every 2 weeks, and vaccination status was collected through linkage to the National Immunisations Management System and questionnaires. Participants had fortnightly asymptomatic SARS-CoV-2 PCR testing and monthly antibody testing, and all tests (including symptomatic testing) outside SIREN were captured. Data cutoff for this analysis was Feb 5, 2021. The follow-up period was Dec 7, 2020, to Feb 5, 2021. The primary outcomes were vaccinated participants (binary ever vacinated variable; indicated by at least one vaccine dose recorded by at least one of the two vaccination data sources) for the vaccine coverage analysis and SARS-CoV-2 infection confirmed by a PCR test for the vaccine effectiveness analysis. We did a mixed-effect logistic regression analysis to identify factors associated with vaccine coverage. We used a piecewise exponential hazard mixed-effects model (shared frailty-type model) using a Poisson distribution to calculate hazard ratios to compare time-to-infection in unvaccinated and vaccinated participants and estimate the impact of the BNT162b2 vaccine on all PCR-positive infections (asymptomatic and symptomatic). This study is registered with ISRCTN, number ISRCTN11041050, and is ongoing. Findings 23 324 participants from 104 sites (all in England) met the inclusion criteria for this analysis and were enrolled. Included participants had a median age of 46·1 years (IQR 36·0–54·1) and 19 692 (84%) were female; 8203 (35%) were assigned to the positive cohort at the start of the analysis period, and 15 121 (65%) assigned to the negative cohort. Total follow-up time was 2 calendar months and 1 106 905 person-days (396 318 vaccinated and 710 587 unvaccinated). Vaccine coverage was 89% on Feb 5, 2021, 94% of whom had BNT162b2 vaccine. Significantly lower coverage was associated with previous infection, gender, age, ethnicity, job role, and Index of Multiple Deprivation score. During follow-up, there were 977 new infections in the unvaccinated cohort, an incidence density of 14 infections per 10 000 person-days; the vaccinated cohort had 71 new infections 21 days or more after their first dose (incidence density of eight infections per 10 000 person-days) and nine infections 7 days after the second dose (incidence density four infections per 10 000 person-days). In the unvaccinated cohort, 543 (56%) participants had typical COVID-19 symptoms and 140 (14%) were asymptomatic on or 14 days before their PCR positive test date, compared with 29 (36%) with typical COVID-19 symptoms and 15 (19%) asymptomatic in the vaccinated cohort. A single dose of BNT162b2 vaccine showed vaccine effectiveness of 70% (95% CI 55–85) 21 days after first dose and 85% (74–96) 7 days after two doses in the study population. Interpretation Our findings show that the BNT162b2 vaccine can prevent both symptomatic and asymptomatic infection in working-age adults. This cohort was vaccinated when the dominant variant in circulation was B1.1.7 and shows effectiveness against this variant. Funding Public Health England, UK Department of Health and Social Care, and the National Institute for Health Research.

A multifunctional efficiency metric is developed using mean-field micromechanics solutions to quantify the multifunctionality of the multifunctional composite anodes. Multifunctional efficiency metrics evaluate the volume and/or mass savings or performance increase when structural and functional materials are replaced by multifunctional materials [1]. The proposed methodology compares the total energy associated with different functionalities, such as elastic strain energy and electric charge energy of the multifunctional materials with the total energy of the single function structural and functional material. To achieve volume and mass savings, the energy of different functionalities is set to be the same between the multifunctional and traditional single- functional materials, and, at the same time, the volume and/or mass of the multifunctional composite needs to be smaller than that of the combination of single- functional materials. The volumes and/or mass savings can be expressed using the properties of multifunctional and traditional single-functional materials. In this work, structural anodes made from silicon nanoparticles, reduced graphene oxide, and aramid nanofibers are used as an example to calculate the mass savings compared to a traditional anode with structural support. The existing multifunctionality metrics are based on the rule of mixtures method, which is adequate for certain geometries and loading conditions, such as in-plane directions for laminate composites. However, if multifunctional composite materials involve multiple phases, material property variation during the charging process, and complex geometries or orientations of the structural and functional phases, a more comprehensive method is required to accurately capture the multifunctional efficiency. The multifunctional efficiency varies significantly during the charging and discharging process. This new metric can provide both upper and lower bounds of multifunctional efficiency. This new multifunctional efficiency metric will help optimize the selection and arrangement of different phases in the multifunctional and quantify the optimization results.

Millions of distinct metal-organic frameworks (MOFs) can be made by combining metal nodes and organic linkers. At present, over 90,000 MOFs have been synthesized and over 500,000 predicted. This raises the question whether a new experimental or predicted structure adds new information. For MOF chemists, the chemical design space is a combination of pore geometry, metal nodes, organic linkers, and functional groups, but at present we do not have a formalism to quantify optimal coverage of chemical design space. In this work, we develop a machine learning method to quantify similarities of MOFs to analyse their chemical diversity. This diversity analysis identifies biases in the databases, and we show that such bias can lead to incorrect conclusions. The developed formalism in this study provides a simple and practical guideline to see whether new structures will have the potential for new insights, or constitute a relatively small variation of existing structures., At present there are databases with over 500,000 predicted or synthesized MOF structures, yet a method to establish whether a new material adds new information does not exist. Here the authors propose a machine-learning based approach to quantify the structural and chemical diversity in common MOF databases.

The limited understanding of the effect of pre-and post-harvest techniques still hinders the full exploitation of seaweed. Here, the effect of harvest site, long term storage and species on the elemental composition, fatty acid profile, lipid content, and antioxidant properties were determined in eight intertidal seaweed species common to Scotland, harvested for potential food application and stored for up to 128 weeks. Result showed that the most significant variation was due to species, with no statistical link found for the combined interaction effect of both storage duration and harvest site in most cases, except for the antioxidant parameters and some selected elements, which was limited to some seaweed species. Overall, our result showed that the chemical profiles of the seaweed species studied were remarkably consistent and unaffected by long term storage. Thus, suggesting that seaweeds sampled from Scotland could be a valuable resource for the development of functional foods.

Energy storage materials that also provide structural integrity are needed to decrease the weight of electrically powered ground and air vehicles. Toward this end, structural supercapacitor electrodes consisting of aramid nanofiber (ANF) and reduced graphene oxide (rGO) were reported in our previous work. Surprisingly, the experimentally measured tensile moduli of these rGO/ANF nanocomposites were not bounded by the experimentally measured moduli of the ANF and rGO materials and were an order of magnitude lower than those of Kevlar fibers and graphene sheets. The purpose of the present work is to develop a micromechanics model for elastic moduli to support the development of rGO/ANF multifunctional composite electrodes. Both the ANF and the rGO are transversely isotropic, wavy and randomly oriented, and no traditional isotropic polymeric matrix is present. We are aware of no existing micromechanics model that is applicable to such a composite. The Mori–Tanaka model is used three times, to model the rGO and ANF separately, and then the rGO/ANF composite films. The model predictions of elastic moduli were compared with experimental results. Waviness was found to be the main factor controlling the effective composite moduli, due to the extreme anisotropy of the rGO. This implies that the effective elastic moduli of rGO/ANF composites can be considerably increased by developing processing methods that reduce waviness. The experimentally observed unbounded moduli were attributed to the relationship between waviness and the volume fraction of the ANF.

OBJECTIVE In surgical training, most assessment tools focus on advanced clinical decision-making or operative skill. Available tools often require significant investment of resources and time. A high stakes oral examination is also required to become board-certified in surgery. We developed Individual Clinical Evaluation (ICE) to evaluate intern-level clinical decision-making in a time- and cost-efficient manner, and to introduce the face-to-face evaluation setting. DESIGN Intern-level ICE consists of 3 clinical scenarios commonly encountered by surgical trainees. Each scenario was developed to be presented in a step-by-step manner to an intern by an attending physician or chief resident. The interns had 17 minutes to complete the face-to-face evaluation and 3 minutes to receive feedback on their performance. The feedback was transcribed and sent to the interns along with incorrect answers. Eighty percent correct was set as a minimum to pass each scenario and continue with the next one. Interns who failed were retested until they passed. Frequency of incorrect response was tracked by question/content area. After passing the 3 scenarios, interns completed a survey about their experience with ICE. SETTING Beth Israel Deaconess Medical Center, an academic tertiary care facility located in Boston, Massachusetts. PARTICIPANTS All first-year surgery residents in our institution (n = 17) were invited to complete a survey. RESULTS All 2016-2017 surgical interns (17) completed the ICEs. A total of $171 (US) was spent conducting the ICEs, and an average of 17 minutes was used to complete each evaluation. In total, 5 different residents failed 1 scenario, with the most common mistake being: failing to stabilize respiration before starting management. After completing the 3 clinical scenarios, more than 90% of respondents agreed or strongly agreed that the evaluations were appropriately challenging for training level, and that the evaluations helped to identify personal strengths and weaknesses in skill and knowledge. The majority believed their knowledge improved as a result of the ICE and felt better prepared to manage these scenarios (88% and 76%, respectively). CONCLUSIONS The ICE is an inexpensive and time efficient way to introduce interns to board type examinations and assess their preparedness for perioperative patient care issues. Common errors were identified which were able to inform educational efforts. ICEs were well accepted by residents. Next steps include extension of the ICE to PGY2 and PGY3 residents.

Silicon oxide substrates underwent gas-phase functionalization with various aminosilanes, and the resulting surfaces were evaluated for their suitability as a solid support for solid phase peptide synthesis (SPPS). APTES (3-aminopropyltriethoxysilane), APDEMS (3-aminopropyldiethoxymethylsilane), and APDIPES (3-aminopropyldiisopropylethoxysilane) were individually applied to thermal oxide-terminated silicon substrates via gas-phase deposition. Coated surfaces were characterized by spectroscopic ellipsometry (SE), contact angle goniometry, X-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), and spectrophotometry. Model oligopeptides with 16 residues were synthesized on the amino surfaces, and the chemical stabilities of the resulting surfaces were evaluated against a stringent side chain deprotection (SCD) step, which contained trifluoroacetic acid (TFA) and trifluoromethanesulfonic acid (TFMSA). Functionalized surface thickness loss during SCD was most acute for APDIPES and the observed relative stability order was APTESAPDEMSAPDIPES. Amino surfaces were evaluated for compatibility with stepwise peptide synthesis where complete deprotection and coupling cycles are paramount. Model trimer syntheses indicated that routine capping of unreacted amines with acetic anhydride significantly increased purity as measured by MALDI-MS. An inverse correlation between the amine loading density and peptide purity was observed. In general, peptide purity was highest for the lowest amine density APDIPES surface.

The goal of this research is to establish a highly compact on-demand release platform for functional materials where porous nanofibers serve as the host, heat-based release trigger and temperature controller for regulated release. The ability to store functional materials in fibers and release them on demand via external signals may open up new frontiers in areas such as smart textiles and autonomous composites. The host material was porous carbon nanofibers (CNFs), which encapsulated functional materials, protected by a thin polymeric coating to thermally regulate the release. This platform was used to store Gentian violet (GV), an antibacterial material, and release it with highly controllable rates in aqueous environment. The high porosity of the CNF yarns, both inter- and intra-fiber porosity, resulted in a mass loading of as high as ∼50 wt%. The active release was triggered via passing electrical signals through CNF yarn backbone, thereby heating the coating. The rate of release as a function of temperature was measured. It was concluded that the release mechanism is via thermally augmented and reversible diffusion rates of GV and water through the coating. By applying electric current, the diffusion coefficient of the coating was increased, and the release rate dramatically increased in a reversible fashion by as much as 39×.

The emerging research field of structural batteries aims to combine the functions of load bearing and energy storage to improve system-level energy storage in battery-powered vehicles and consumer products. Structural batteries, when implemented in electric vehicles, will be exposed to greater temperature fluctuations than conventional batteries in electric vehicles. However, there is a lack of knowledge in public domains and scientific literature regarding how these thermal boundary conditions impact power capabilities of the structural batteries. To fill this gap, the present work simulates the transient temperature-dependent specific power capabilities of a high aspect ratio structural battery composite by solving the one-dimensional heat transfer equation with heat source terms and convective boundary conditions. Equivalent circuit modeling of resistivity-induced losses is used with a second-order finite difference method to examine battery performance. More than 60 different run configurations are evaluated in this work, examining how thermal boundary conditions and internal heat generation influence power capabilities and multifunctional efficiency of the structural battery. The simulated structural battery composite is shown to have good specific Young’s modulus (79.5%–80.3% of aluminum), a specific energy of 158 Wh kg−1, and specific power of 41.2–55.2 W kg−1, providing a multifunctional efficiency of 1.15–1.17 depending on configuration and thermal loading conditions and demonstrating the potential of load-bearing structural batteries to achieve mass savings. This work emphasizes the dependency of power efficiency on cell design and external environmental conditions. Insulating material is shown to improve multifunctional efficiency, particularly for low ambient temperatures. It is demonstrated that as cell temperature increases due to high ambient temperature or heat generation in the battery, the specific power efficiency increases exponentially due to a favorable nonlinear relation between ionic conductivity and cell temperature. The simulations also demonstrate a thermal feedback loop where resistivity-induced power losses can lead to self-regulation of cell temperature. This effect reduces run-averaged losses, particularly at low ambient temperatures.

We report the syntheses and structures of five metal–organic frameworks (MOFs) based on transition metals (NiII, CuII, and ZnII), adenine, and di-, tri-, and tetra-carboxylate ligands. Adenine, with multiple N donor sites, was found to coordinate to the metal centers in different binding modes including bidentate (through N7 and N9, or N3 and N9) and tridentate (through N3, N7, and N9). Systematic investigations of the protonation states of adenine in each MOF structure via X-ray photoelectron spectroscopy revealed that adenine can be selectively protonated through N1, N3, or N7. The positions of H atoms connected to the N atoms were found from the electron density maps, and further supported by the study of C–N–C bond angles compared to the literature reports. DFT calculations were performed to geometrically optimize and energetically assess the structures simulated with different protonation modes. The present study highlights the rich coordination chemistry of adenine and provides a method for the determination of its protonation states and the location of protonated N atoms of adenine within MOFs, a task that would be challenging in complicated adenine-based MOF structures., The protonation states and positions of hydrogen atoms in five adenine-based metal−organic frameworks were revealed using geometrical studies based on single-crystal XRD data supported by XPS spectra and DFT calculations.

WOS: 000430087100013, Shape memory alloy pipe couplers use the shape memory effect to apply a contact pressure onto the surface of the pipes to be coupled. In the current research, a shape memory alloy pipe coupler is designed, fabricated, and tested. An in-house developed NiTi alloy is used for the coupler. The coupler is initially designed using finite element as well as analytical modeling to accommodate the required actuation temperature and contact pressure properties. The coupling pressure is then measured using strain gages mounted on the internal surface of an elastic steel ring. The thermal actuation response of the coupler is measured under both stressed and stress-free conditions. In addition, the state of anisotropy is investigated in the coupler by characterizing samples in the longitudinal and transverse directions. The NiTi coupler demonstrates a multiple-actuation response and a high contact pressure. The results show no change in transformation temperatures with respect to two perpendicular transverse and longitudinal directions. However, the material can undergo higher transformation strains in the longitudinal direction.

Shape memory alloy actuators deliver high forces while being compact and reliable, making them ideal for consideration in aerospace applications. Induction heating of shape memory alloy actuators, specifically tubes that twist about the longitudinal axis, has recently been studied experimentally and computationally using finite element analysis. Reduced-order models for the torsional behavior of shape memory alloy tubes and induction heating of general metallic tubes exist, and thus, it is possible for these thermal and mechanical models to be combined and numerically solved. This work develops and implements an engineering model for inductively heated shape memory alloy tubes based on the reduction of the governing partial differential equations in space and time to an ordinary differential equation in time. An example solution is compared to finite element analysis results and agrees well. Finally, the ordinary differential equation is linearized and solved analytically. The linearized model agrees well with the nonlinear ordinary differential equation and finite element model.

A novel sequential processing approach to fabricate versatile fibres containing encapsulated materials is presented. It is based on developing highly porous fibres, to be filled with functional materials and coated with protective layers. Applicability of the approach to develop porous poly(methyl methacrylate) (PMMA) fibres with encapsulated antibacterial salts within a coating is demonstrated. The salt was introduced to the fibre via a sacrificial solvent. Desired solvent properties to ensure successful filling was discussed. The salt was encapsulated via spray coating. The coating characteristics were tuned via vapour treatment to facilitate controllable radial salt release. Large volume axial release was also achieved due to the axial pore connectivity. Compared to state-of-the-art methods to produce fibres with functional material inclusions such as emulsion electrospinning, the method presented herein, due to its sequential processing nature, offers greater freedom in material selection and thus broad applications of the fibres.

Constitutive models are necessary to design shape memory alloy (SMA) components at nano- and micro-scales in NEMS and MEMS. The behavior of small-scale SMA structures deviates from that of the bulk material. Unfortunately, this response cannot be modeled using conventional constitutive models which lack an intrinsic length scale. At small scales, size effects are often observed along with large gradients in the stress or strain. Therefore, a gradient-based thermodynamically consistent constitutive framework is established. Generalized surface and body forces are assumed to contribute to the free energy as work conjugates to the martensite volume fraction, transformation strain tensor, and their spatial gradients. The rates of evolution of these variables are obtained by invoking the principal of maximum dissipation after assuming a transformation surface, which is a differential equation in space. This approach is compared to the theories that use a configurational force (microforce) balance law. The developed constitutive model includes energetic and dissipative length scales that can be calibrated experimentally. Boundary value problems, including pure bending of SMA beams and simple torsion of SMA cylindrical bars, are solved to demonstrate the capabilities of this model. These problems contain the differential equation for the transformation surface as well as the equilibrium equation and are solved analytically and numerically. The simplest version of the model, containing only the additional gradient of martensite volume fraction, predicts a response with greater transformation hardening for smaller structures.

Locally resonant metamaterials are capable of demonstrating low-frequency vibration absorption due to the formation of stop-bands. In this work, the multi-mode vibration absorption capability of an adaptive nonlinear metamaterial beam is investigated. The metamaterial beam is idealized as a hinged-hinged finite Euler-Bernoulli beam with a von-Kármán geometric type nonlinearity that is attached to a distributed cellular array of shape memory alloy (SMA) spring–mass resonators. Numerical studies are performed to evaluate the effects of dissipation and change in elastic modulus due to material phase change of SMA pseudoelasticity on the dynamic response of the beam. Using a modal analysis approach, stop-bands are generated at the first three nonlinear frequencies of the beam. The frequency response demonstrates a hardening behavior at a temperature significantly higher than the austenite finish temperature while conversely demonstrating a softening behavior at a temperature slightly above the austenite finish temperature.

Sustained, quantitative observations of nearshore waves and sand levels are essential for testing beach evolution models, but comprehensive datasets are relatively rare. We document beach profiles and concurrent waves monitored at three southern California beaches during 2001–2016. The beaches include offshore reefs, lagoon mouths, hard substrates, and cobble and sandy (medium-grained) sediments. The data span two energetic El Niño winters and four beach nourishments. Quarterly surveys of 165 total cross-shore transects (all sites) at 100 m alongshore spacing were made from the backbeach to 8 m depth. Monthly surveys of the subaerial beach were obtained at alongshore-oriented transects. The resulting dataset consists of (1) raw sand elevation data, (2) gridded elevations, (3) interpolated elevation maps with error estimates, (4) beach widths, subaerial and total sand volumes, (5) locations of hard substrate and beach nourishments, (6) water levels from a NOAA tide gauge (7) wave conditions from a buoy-driven regional wave model, and (8) time periods and reaches with alongshore uniform bathymetry, suitable for testing 1-dimensional beach profile change models., Design Type(s)database creation objective • modeling and simulation objectiveMeasurement Type(s)bathymetry and wavesTechnology Type(s)OceanographyFactor Type(s)geographic locationSample Characteristic(s)San Diego • ocean Machine-accessible metadata file describing the reported data (ISA-Tab format)