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Bioadhesives are essential for tissue adhesion and regeneration. Optimal bioadhesive should possess elasticity, robust adhesion capabilities in wet environments, and a cytocompatible scaffold for cell regeneration. Current options like cyanoacrylates and fibrin glues fail in these aspects due to cell toxicity and poor moisture adhesion, prompting the need for new materials that reconcile cytocompatibility with robust adhesion. These limitations by available commercial bioadhesives, demand the development of new adhesive biomaterials that combine cytocompatibility with strong adhesion. Marine organisms such as mussels secrete proteins that adhere effectively even underwater, but the adhesion mechanisms remain partly elusive. These proteins' adhesion strength is largely attributed to catechol side chains of L-Dopa, which can form various surface interactions, including hydrogen bonding and metal coordination. Commercial use of natural adhesive proteins is time- and labor-demanding, and uneconomical, as it takes thousands of mussel specimens to extract just one gram of adhesive proteins. In addition, low expression yield, low purification yield, and high levels of post-purification insolubility, restrict the production of recombinant foot protein types in Escherichia coli. To overcome these issues and inspired by intrinsically disordered domains of tropoelastin, the soluble precursor of elastin, elastin-like polypeptides (ELPs) consist of repeated sequences of the pentapeptide motif “VPGXG” (with “X” representing any amino acids except proline), emerge as promising synthetic alternatives. These stimuli-responsive adhesives exhibit a reversible phase transition regulated by temperature, making them suitable for applications such as drug delivery and wound healing. Their lower critical solution temperature (LCST) can be genetically adjusted to just below human body temperature, offering versatility for medical use. The bioadhesive efficacy of ELPs is linked to Dopa, cruc

Disposable paper (DP) cups, a staple in on-the-go beverage culture, contribute to environmental challenges due to their non-biodegradable polyethylene (PE) liners. This research presents an eco-friendly alternative by harnessing fungal mycelium combined with North American wetland biomass. The study evaluates three fungal species—Ganoderma lucidum, Pleurotus ostreatus, and Polyporus squamosus—cultivated on canola straw (Brassica napus L.) and cattail substrates (Typha latifolia) to produce mycelium composite materials. Among these, Ganoderma lucidum demonstrated superior mycelial growth and structural integrity when paired with cattail substrate over a 14-day period. Initial growth assessment was conducted using Potato Dextrose Agar (PDA), with further optimization through Yeast Extract Peptone Dextrose Broth (YEPDB) liquid media. The research explored the production of compostable coffee cups and mycelium sheets using a 3D poly-lactic acid (PLA) mold and aluminum foil, respectively. Mycelium composites were harvested at two growth intervals (2 weeks and 4 weeks) and analyzed for their morphological, chemical, thermo-mechanical, crystallinity, thermodynamic, and mechanical properties. The resulting composites exhibited notable thermal stability exceeding 267°C, low thermal conductivity (0.03-0.04 Wm⁻¹K⁻¹), and inherent hydrophobicity with a water contact angle surpassing at 100°. However, the mechanical properties, such as Young's modulus, were significantly lower than those of commercial coffee cup paper, with values of 11.27 MPa and 80.91 MPa for the 2-week and 4-week samples, respectively, compared to 1349.35 MPa for standard coffee cup paper. These findings demonstrate that cattail can serve as a viable substrate for producing mycelium-based bio-composites, suitable for applications requiring thermal stability and hydrophobicity.

The transportation of crude oil across Canada leads to a risk of accidental spills into freshwater environments. Conventional cleanup methods can exacerbate the negative effects of oil spills and delay ecosystem recovery. A less-invasive alternative is the use of engineered floating wetlands (EFWs) – vegetated platforms which promote microbial colonization and biofilm formation in their underwater root-zones – to enhance the biodegradation of spilled oil. This thesis assessed the efficacy of EFWs for removing oil-derived polycyclic aromatic compounds (PACs) from fresh water and the effects of plant species composition and nutrient addition carbon to phosphorus (C:P) ratio on EFW function. Twenty-six (26) ~1550 L mesocosms containing EFWs were exposed to equal-volume spills of water-accommodated fraction (WAF) produced by weathering conventional heavy crude oil (CHV). The EFWs were either planted with a different composition of Typha sp., Carex atherodes, and C. lasiocarpa or had an even species composition and were amended with slow-release fertilizer to achieve a target C:P ratio, based on the carbon content of the WAF. Concentrations of PACs decreased rapidly, with 96.8% of compound classes across the mesocosms declining to baseline concentrations within the first 10 days of the 96-day exposure. There was no evidence to indicate that EFWs had an appreciable effect on PAC removal or that changes in plant species composition or C:P ratio affected EFW function. There were no consistent significant effects of WAF, plant presence, plant species, or C:P ratio on the activity of microbial biofilm or the composition and diversity of the prokaryotic and eukaryotic microbial communities in the root-zone. Results were confounded by low initial PAC concentrations, possibility of PAC sorption to mesocosm plastic, flaws in sample event timing, and tadpole grazing on root biofilm; future research which addresses these experimental limitations is required to support the incorpora

Clostridium thermocellum, is an anaerobic, cellulolytic bacterium (cellulose hydrolysis specialist) with the ability to ferment the released mono- or oligomeric sugars to multiple bioproducts, including ethanol. The low yield in ethanol can be attributed to three factors: the branched fermentation pathway, thermodynamic bottlenecks at key points in the glycolysis pathway, and redox balancing centered around redox cofactors. Heterologous expression of an ATP-dependent phosphofructokinase (PfkA) has been a suggested solution to overcome the upper glycolysis bottleneck, caused by the highly expressed pyrophosphate-dependent phosphofructokinase. However, C. thermocellum inherently expresses a PfkA, as well as a fructokinase, both characterized to utilize either ATP or GTP. The latter two genes show low expression levels when grown on model substrates; therefore alternate substrates were queried for potential upregulation of PfkA. C. thermocellum metabolism is generally studied using cellobiose as the sole carbon source to understand carbon and electron flux to fermentation end-products. Adaptive growth on glucose and sorbitol was performed, resulting in a ~2.5-fold and ~4.5-fold increase in ethanol yield, compared to the wild-type strain fermenting cellobiose. Initial expectations were that fermentation of sorbitol would produce higher ethanol and hydrogen concentrations by virtue of the sugar alcohol being a more reduced substrate in comparison to cellobiose, but the reason for the increase during glucose fermentation required investigation. The increase in ethanol yield was accompanied by a decrease in canonical end- products, most notably lactate for glucose adapted strains, while acetate, lactate, and formate decreased for sorbitol adapted strains. The stable fermentation profiles for adapted strains were disrupted after a single passage with cellobiose. The shift in end-products still maintained a higher ethanol yield compared to wild type strains, suggesting that

Anaerobic digestion (AD) has shown the potential to reduce the abundance of antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) in animal manures. It stands as a promising option to reduce the risk of the spread of antimicrobial resistance (AMR) due to livestock production and manure applications. However, the underlying mechanisms driving these changes still need to be fully understood. This multidisciplinary study aimed to utilize metagenomics to investigate the molecular and microbial mechanisms associated with the evolution of ARGs and MGEs during the anaerobic digestion (AD) of bovine dairy manure. The research focused on three main aspects: 1) examining the long-term effects of mesophilic (MAD) and thermophilic (TAD) anaerobic digestion on the entire set of ARGs (resistome) and MGEs (mobilome) in manure; 2) comparing the impact of alternative manure treatments, such as storage and solid-liquid separation, on resistomes and mobilomes; 3) identifying microbial groups potentially associated with ARGs and MGEs and microbial shifts potentially driving changes in resistomes and mobilomes. A meta-analysis conducted early in this research informed the primary focus of this research. Two anaerobic digesters operating at mesophilic (36 °C) and the other at thermophilic (55 °C) temperatures were set up, operated, monitored, and studied for 4 and 2 years, respectively. Metagenomics analyses were used to evaluate resistomes, mobilomes, and microbiomes in the mesophilic and thermophilic digesters operating under steady state and in the bovine manure used as substrate. The results indicated that MAD and TAD lowered ARG levels in fresh cattle manure by over 50% and MGEs by over 65%. Surprisingly, TAD did not outperform MAD at reducing ARGs and MGEs. Co-occurrence analysis indicated a strong association between microbial groups from the phyla Bacillota (e.g., Jeotgalicoccus, Streptococcus, Enterococcus), Actinomycetota (e.g., Brevibacterium, Rhodococcus)

We propose a reduced space mixed finite element method (MFEM) built on a Skinning Eigenmode subspace and material-aware cubature scheme. Our solver is well-suited for simulating scenes with large material and geometric heterogeneities in real-time. This mammoth geometry is composed of 98,175 vertices and 531,565 tetrahedral elements and with a heterogenous composition of widely varying materials of muscles ($E= 5\times10^5$ Pa), joints ($E=1\times10^5$ Pa), and bone ($E=1\times10^{10}$ Pa). The resulting simulation runs at 120 frames per second (FPS)., Comment: 10 pages, 15 figures

This paper demonstrates that the space of piecewise smooth functions can be well approximated by the space of functions defined by a set of simple (non-linear) operations on smooth uniform splines. The examples include bivariate functions with jump discontinuities or normal discontinuities across curves, and even across more involved geometries such as a 3-corner. The given data may be uniform or non-uniform, and noisy, and the approximation procedure involves non-linear least-squares minimization. Also included is a basic approximation theorem for functions with jump discontinuity across a smooth curve.

On-line learning presents significant new challenges for faculty, students, and the colleges and universities where they teach and learn. The overriding challenge for all parties is to ensure that technology is used to enhance, not degrade teaching and learning. DePaul University, Illinois, which grew from two to six campuses, expanded the role of the Office of Distance Learning to include faculty development in the use of distance learning technologies. The Naperville campus was planned as a "high tech" campus--many services will be available at the new campus principally via technology. An intensive 4-day summer workshop immersed faculty in online learning tools. It was discovered that it was probably a mistake to promote the view that these technologies extend the classroom, rather than create new learning environments. The use of technology for teaching and learning requires that faculty are given more support in the development of learning activities employing these technologies. Developing and conducting on-line discussions that result in significant learning takes time. Open-ended discussions such as those that occur in listservs and newsgroups have their place as a component of computer-mediated courses, but most learning occurs when learning activities are structured. The role of the instructor needs to be clearly understood and communicated to the students. At times she is the discussion leader; at other times the facilitator; and sometimes an evaluator. (RS)

Bakgrund: Överrapportering i slutenvården är ett kritiskt moment som utförs dagligen vid skiftbyte där god kommunikation är grundläggande för patientsäkerheten. Traditionellt sker överrapporteringen på sjuksköterskeexpeditionen utan patientens delaktighet. Bedside-rapportering är en relativt ny metod där överrapporteringen sker i samråd med patienten bredvid sängkanten vilket kan främja patientdelaktigheten och en säker vård. Eftersom den relativt nya metoden inte används som standard i slutenvården är det viktigt att undersöka sjuksköterskors erfarenheter av den. Syfte: Att beskriva sjuksköterskors erfarenheter av bedside-rapportering i slutenvården. Metod: En allmän litteraturöversikt som följer Polit och Becks niostegsmodell. Sökning efter artiklar utfördes på databaserna CINAHL och Pubmed. Data analyserades med Graneheim och Lundmans kvalitativa innehållsanalys. Resultat: Resultatet framställde tre kategorier och sex tillhörande underkategorier: “Hantering av känslig information”, “Kommunikationsflödet” och “Modifierade tillvägagångssätt”. Resultatet visade att sjuksköterskor upplevde utmaningar att hantera känslig information och att tidsåtgången var en oro. Många föredrog ett modifierat tillvägagångsätt. Slutsats: Sjuksköterskor upplever flera hinder med implementeringen av bedside-rapportering i slutenvården, inklusive ineffektivitet, sekretesshantering och val av tillvägagångssätt. Sjuksköterskorna anser att dessa faktorer behöver bearbetas för att metoden ska kunna tillämpas på ett säkert sätt. Samtidigt beskrivs även upplevelser av att bedside-rapportering främjar patientsäkerhet och delaktighet i omvårdnadsprocessen., Background: Handover in inpatient health care is a critical procedure performed daily, where effective communication is fundamental to patient safety. Traditionally, handovers occur in the nurse’s station without patient involvement. Bedside-handover is a relatively new approach where handover takes place in consultation with the patient at the bedside, promoting patient engagement and safe care. As this relatively new method is not yet a standard practice in inpatient care, it is important to investigate nurses’ experiences with it. Aim: To describe nurses’ experiences of bedside-handover in inpatient care. Method: A general literature review following Polit and Beck’s nine-step model. Article searches were conducted in the CINAHL and PubMed databases. Data were analyzed using Graneheim and Lundman’s qualitative content analysis. Result: The findings resulted in three categories and nine corresponding subcategories: “Management of sensitive information”, “Communication flow” and “Modified approaches”. The findings indicated that nurses faced challenges related to handling sensitive information and expresses concerns about time constraint. Nurses faced challenges related to sensitive information and expressed concerns about time consumption. Many preferred a modified approach. Many preferred a modified approach. Summary: Nurses experience several obstacles in implementing bedside-handover in inpatient health care, including inefficiency, confidentiality management and choice of approach. Nurses believe these factors require more work to be applied in a safe way. Nonetheless, experiences of bedside-handover promoting patient safety and participation in the nursing process were also described.

Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental good practice stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.

Physical systems ranging from elastic bodies to kinematic linkages are defined on high-dimensional configuration spaces, yet their typical low-energy configurations are concentrated on much lower-dimensional subspaces. This work addresses the challenge of identifying such subspaces automatically: given as input an energy function for a high-dimensional system, we produce a low-dimensional map whose image parameterizes a diverse yet low-energy submanifold of configurations. The only additional input needed is a single seed configuration for the system to initialize our procedure; no dataset of trajectories is required. We represent subspaces as neural networks that map a low-dimensional latent vector to the full configuration space, and propose a training scheme to fit network parameters to any system of interest. This formulation is effective across a very general range of physical systems; our experiments demonstrate not only nonlinear and very low-dimensional elastic body and cloth subspaces, but also more general systems like colliding rigid bodies and linkages. We briefly explore applications built on this formulation, including manipulation, latent interpolation, and sampling., Comment: SIGGRAPH 2023

This paper introduces a novel graph-based filter method for automatic feature selection (abbreviated as GB-AFS) for multi-class classification tasks. The method determines the minimum combination of features required to sustain prediction performance while maintaining complementary discriminating abilities between different classes. It does not require any user-defined parameters such as the number of features to select. The methodology employs the Jeffries-Matusita (JM) distance in conjunction with t-distributed Stochastic Neighbor Embedding (t-SNE) to generate a low-dimensional space reflecting how effectively each feature can differentiate between each pair of classes. The minimum number of features is selected using our newly developed Mean Simplified Silhouette (abbreviated as MSS) index, designed to evaluate the clustering results for the feature selection task. Experimental results on public data sets demonstrate the superior performance of the proposed GB-AFS over other filter-based techniques and automatic feature selection approaches. Moreover, the proposed algorithm maintained the accuracy achieved when utilizing all features, while using only $7\%$ to $30\%$ of the features. Consequently, this resulted in a reduction of the time needed for classifications, from $15\%$ to $70\%$., Comment: 8 pages, 4 figures

In this work we present a new WENO b-spline based quasi-interpolation algorithm. The novelty of this construction resides in the application of the WENO weights to the b-spline functions, that are a partition of unity, instead to the coefficients that multiply the b-spline functions of the spline. The result obtained conserves the smoothness of the original spline and presents adaption to discontinuities in the function. Another new idea that we introduce in this work is the use of different base weight functions from those proposed in classical WENO algorithms. Apart from introducing the construction of the new algorithms, we present theoretical results regarding the order of accuracy obtained at smooth zones and close to the discontinuity, as well as theoretical considerations about how to design the new weight functions. Through a tensor product strategy, we extend our results to several dimensions. In order to check the theoretical results obtained, we present an extended battery of numerical experiments in one, two and tree dimensions that support our conclussions.

In many applications, it is useful to use piecewise polynomials that satisfy certain regularity conditions at the joint points. Cubic spline functions emerge as good candidates having C2 regularity. On the other hand, if the data points present discontinuities, the classical spline approximations produce Gibbs oscillations. In a recent paper, we have introduced a new nonlinear spline approximation avoiding the presence of these oscillations. Unfortunately, this new reconstruction loses the C2 regularity. This paper introduces a new nonlinear spline that preserves the regularity at all the joint points except at the end points of an interval containing a discontinuity, and that avoids the Gibbs oscillations.

Buesseler, K., Jin, D., Kourantidou, M., Levin, D., Ramakrishna, K., Renaud, P., Ausubel, J., Baltes, K., Gjerde, K., Holland, M., Kostel, K., LaCapra, V., Martin, A., Sosik, H., Thorrold, S., Tierney, T., Joyce, K., Renier, N., Taylor, E. (2022). The Ocean Twilight Zone’s Role in Climate Change. Woods Hole Oceanographic Institution, 32 pp., The ocean twilight zone (more formally known as the mesopelagic zone) plays a fundamental role in global climate. It is the mid-ocean region roughly 100 to 1000 meters below the surface, encompassing a half-mile deep belt of water that spans more than two-thirds of our planet. The top of the ocean twilight zone only receives 1% of incident sunlight and the bottom level is void of sunlight. Life in the ocean twilight zone helps to transport billions of metric tons (gigatonnes) of carbon annually from the upper ocean into the deep sea, due in part to processes known as the biological carbon pump. Once carbon moves below roughly 1000 meters depth in the ocean, it can remain out of the atmosphere for centuries to millennia. Without the benefits of the biological carbon pump, the atmospheric CO 2 concentration would increase by approximately 200 ppm 1 which would significantly amplify the negative effects of climate change that the world is currently trying to curtail and reverse. Unfortunately, existing scientific knowledge about this vast zone of the ocean, such as how chemical elements flow through its living systems and the physical environment, is extremely limited, jeopardizing the efforts to improve climate predictions and to inform fisheries management and ocean policy development., Funding is: The Audacious Project housed at TED

An integrated model was developed to simulate airborne transmission of infectious animal viral diseases. Computational fluid dynamics (CFD), viral infectivity decay, and dose-response models were integrated to simulate physical and biological processes in the aerosol transmission pathway of animal disease. In the first part of this study, a CFD model was developed and validated for simulating movement of bioaerosols of porcine reproductive and respiratory syndrome virus (PRRSV) in laboratory conditions where air flowed from a source to a recipient chamber. The model performed well (normalized mean square error NMSE <0.25) at simulating steady-state PRRSV bioaerosol concentrations, but differences were greater (NMSE >0.25) during the transient stage of airflow. In the second part of this study, a series of dose-response models were performed for five infectious animal viruses on various transmission routes. The transmissibility of animal viruses varied with the transmission route, and aerosol transmission required lower doses to cause infection than intranasal and oral transmission for PRRSV. The CFD model was coupled with aerosol transmission dose-response models for PRRSV. The coupled models predicted probability of infection (82% to 100%), which was in good agreement with observed rates in two experimental studies (84% and 90%). In the third part of this study, an integrated model consisting of CFD, infectivity decay, and dose-response was developed to simulate the aerosol transmission of PRRSV between a source and a recipient building in field conditions, based on an experimental study reported in the literature. CFD was used to model the PRRSV aerosol movement towards and within the recipient building, and the infectivity decay and dose-response models were used to predict the probability of infection upon exposure to the calculated aerosol dose of PRRSV. The integrated model predicted that the aerosol transmission event occurred in the recipient building on a d

Clostridium thermocellum is one of the most promising candidates for consolidated bioprocessing of lignocellulosic biomass to biofuels and chemicals but its low product yield and the presence of unexpected minor fermentation products, such as amino acids, has restricted industrial scale production. Few reports have compared the physiological effects of end-product accumulation and the behavior of C. thermocellum in a natural, consortium setting. This may provide a more detailed understanding of the complex metabolism of C. thermocellum, aiding future engineering efforts to increase product yield. In this study, we grew C. thermocellum in co-culture with Methanothermobacter marburgensis, a hydrogenotrophic methanogen, on cellulose in batch culture at 60 oC to investigate the physiological effects of continuous H2 removal on C. thermocellum. When grown in co-culture, minimal H2 concentration and continuous CH4 production was detected, indicating continuous H2 and CO2 consumption by M. marburgensis. C. thermocellum growth rate did not change significantly, but a faster rate of cellulose hydrolysis was observed. Major end-product profile of C. thermocellum changed with the most notable difference being an increase in acetate, and a decrease in formate and ethanol. Changes in alternate end-products, such as amino acids and TCA cycle intermediates, were also observed. The metabolic shift to H2 and acetate in response to continuous H2 removal was accompanied by changes in the expression of [FeFe] H2ases of C. thermocellum: (a) 10-fold decrease in Cthe_0430, (b) 2-fold decrease in Cthe_0342, (c) 1.5-fold decrease in Cthe_3003. We demonstrated that growth with a naturally occurring hydrogenotrophic partner, such as methanogens, alter the metabolic patterns and H2ase gene expression in C. thermocellum. Low H2 partial pressure required to overcome thermodynamic barriers for the oxidation of reducing equivalents was achieved by continuous H2 removal via methanogen consumption.

Hemostasis is an important issue in-clinic treatments for acute wounds. Existing hemostatic materials may not fully meet the demands in emergency situations in terms of hospitals and battlefields which calls for the development of cost-effective hemostatic materials for clinical applications. Cellulose as a natural polymer is abundant in nature and has been widely used in different applications, like food, cosmetics, and hemostatic applications. Cellulose-based materials can absorb water from blood upon contact with wounds, which helps to stop bleeding. In this work, cellulose-based aerogels and hydrogels were prepared and their potential applications as hemostatic materials were explored. Aerogels with ultra-high porosity and large surface area can absorb water from blood and form barriers in the trauma site to stop bleeding. In this thesis, an aerogel with lightweight, injectability, antibacterial ability, water-induced shape memory behavior, and excellent compressibility was developed from carboxymethylated nanocellulose fibers (NCFs), alginate and zinc chloride. The obtained NCFs-alginate aerogels have dual networks which are the physical network of NCFs formed by freeze-drying and physical crosslinking between alginate and zinc ions. Here, zinc chloride endowed the aerogels with the antibacterial ability to prevent infection and reduce the probability of complications due to microorganisms. The NCFs-alginate aerogels with high water absorption can absorb water when contacting blood to stop bleeding. Meanwhile, in the presence of NCFs and alginate, the aerogels can promote wound healing quickly. Besides, injectability and rapid water-induced shape recovery ability (4s) allowed the NCFs-alginate aerogels to be used for penetrating wounds. Carboxymethylated cellulose (CMC) is an important derivation of cellulose and has been widely used in biomedical applications. A facile and environmentally friendly method for preparing self-healing hydrogels using CMC, polyviny

Fossil-fuel-based insulation materials such as polyvinyl chloride (PVC), low-density polyethylene (LDPE), cross-linked polyethylene (XLPE) and ethylene-vinyl acetate (EVA) have dominated the electrical insulation industry at present. Increased use of these polymers have caused a serious threat to environment causing, environmental pollution, global warming, and climate changes worldwide. Biopolymers offers a solution to these problems, since they are fully renewable from bio-sources such as biomass, agricultural by-products, and biological waste. In order to utilize biopolymers as an electrical insulation material, they should match or exceed electrical, mechanical, and thermal properties of their fossil-fuel-based counterparts. Four bio-polymers namely polyhydroxy butyrate (PHB), poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV), poly (lactic acid) (PLA), cellulose acetate (CA) and three fossil-fuel-based synthetic polymers polycaprolactone (PCL), polybutylene succinate (PBS), poly (butylene adipate-co-terephthalate) (PBAT) are selected based on their popularity in research and commercial availability. Although commercial manufacturing of these four synthetic polymers is from fossil-fuel-based sources, they can be synthesised from bio-sources as well. Samples of six of these selected polymers, PHB, PHBV, PCL, PBS, and PBAT are obtained collaborating with the Biosystems Engineering department for the electrical measurements. These samples are thin films, prepared from spin-casting process. Electrical properties such as complex dielectric constant, volume resistivity and AC electrical breakdown strength of these samples are measured, while thermal and mechanical properties are summarized from literature. Using experimental measurements and the literature data, properties of these selected polymers are compared with conventional polymers such as PVC, LDPE, XLPE and EVA. Few biopolymers are shortlisted as possible candidate materials for electrical insulation applica

Medium chain length (mcl) polyhydroxyalkanoate (PHA) polymers were produced by Pseudomonas putida LS46 from the hydrolysed long-chain fatty acids (LCFAs) of vegetable oils. LCFAs are sustainable and economical substrates for mcl-PHA production which get converted into mcl-PHAs from the microbial fatty acid degradation pathway. As such, good polymer yields have been obtained from fatty acids and their functional groups can be retained in the polymer. The length and degree of unsaturation in the substrate is correlated to the polymer composition. The comparison of mcl-PHA synthesis using octanoic acid or LCFAs of P. putida LS46 in response to microaerophilic conditions differs based on substrate. Grown on octanoic acid, cell division ceased under microaerophilic conditions with carbon flux towards mcl-PHA accumulation. In contrast, growth continued on LCFAs at a linear rate consistent with the growth rate at onset of limitation (0.36 g L-1 h-1) but mcl-PHA accumulation also began to increase. This work demonstrated the differential biochemical response in microaerophilic conditions of P. putida LS46 and indicated that feeding strategies could be designed to improve productivity, tailor polymer properties and reduce production costs. The polymer properties of mcl-PHAs produced using varied carbon substrates were analysed to determine the effect of substrate biochemistry on monomer composition and crystallinity. Significant variations in monomer composition and molecular weights were observed based on substrate, and whether de novo fatty acid synthesis or fatty acid degradation pathways were necessary for metabolism. A relationship between monomer composition and mechanical and thermal properties was observed and reported. Due to the absent crystallinity of mcl-PHAs from unsaturated substrates, alternative applications involving the functionalization from these moieties are required for mcl-PHAs from many LCFAs. We hypothesized that oxidative cleavage of the unsaturated

Given a finite number of samples of a continuous set-valued function F, mapping an interval to compact subsets of the real line, we develop good approximations of F, which can be computed efficiently.

By starting with the assumption that motion is fundamentally a decision making problem, we use the world-line concept from Special Relativity as the inspiration for a novel multi-agent path planning method. We have identified a particular set of problems that have so far been overlooked by previous works. We present our solution for the global path planning problem for each agent and ensure smooth local collision avoidance for each pair of agents in the scene. We accomplish this by modeling the trajectories of the agents through 2D space and time as curves in 3D. Global path planning is solved using a modified Djikstra's algorithm to ensure that initial trajectories for agents do not intersect. We then solve for smooth local trajectories using a quasi-Newton interior point solver, providing the trajectory curves with a radius to turn them into rods. Subsequently, resolving collision of the rods ensures that no two agents are in the same spatial position at the same time. This space-time formulation allows us to simulate previously ignored phenomena such as highly asymmetric interactions in very constrained environments. It also provides a solution for scenes with unnaturally symmetric agent alignments without the need for jittering agent positions or velocities.

We propose a neural network-based approach for collision detection with deformable objects. Unlike previous approaches based on bounding volume hierarchies, our neural approach does not require an update of the spatial data structure when the object deforms. Our network is trained on the reduced degrees of freedom of the object, so that we can use the same network to query for collisions even when the object deforms. Our approach is simple to use and implement, and it can readily be employed on the GPU. We demonstrate our approach with two concrete examples: a haptics application with a finite element mesh, and cloth simulation with a skinned character.

We propose and explore a new, general-purpose method for the implicit time integration of elastica. Key to our approach is the use of a mixed variational principle. In turn its finite element discretization leads to an efficient alternating projections solver with a superset of the desirable properties of many previous fast solution strategies. This framework fits a range of elastic constitutive models and remains stable across a wide span of timestep sizes, material parameters (including problems that are quasi-static and approximately rigid). It is efficient to evaluate and easily applicable to volume, surface, and rods models. We demonstrate the efficacy of our approach on a number of simulated examples across all three codomains.

Given cell-average data values of a piecewise smooth bivariate function $f$ within a domain $\Omega$, we look for a piecewise adaptive approximation to $f$. We are interested in an explicit and global (smooth) approach. Bivariate approximation techniques, as trigonometric or splines approximations, achieve reduced approximation orders near the boundary of the domain and near curves of jump singularities of the function or its derivatives. Whereas the boundary of $\Omega$ is assumed to be known, the subdivision of $\Omega$ to subdomains on which $f$ is smooth is unknown. The first challenge of the proposed approximation algorithm would be to find a good approximation to the curves separating the smooth subdomains of $f$. In the second stage, we simultaneously look for approximations to the different smooth segments of $f$, where on each segment we approximate the function by a linear combination of basis functions $\{p_i\}_{i=1}^M$, considering the corresponding cell-averages. A discrete Laplacian operator applied to the given cell-average data intensifies the structure of the singularity of the data across the curves separating the smooth subdomains of $f$. We refer to these derived values as the signature of the data, and we use it for both approximating the singularity curves separating the different smooth regions of $f$. The main contributions here are improved convergence rates to both the approximation of the singularity curves and the approximation of $f$, an explicit and global formula, and, in particular, the derivation of a piecewise smooth high order approximation to the function.

This booklet is intended as a guide to help foreign students who are studying in the United States. Opportunities for foreign students to study in the United States exist as never before, in every state, at all education levels, and in virtually every discipline and subject field. It is anticipated that the foreign student population in this country, currently numbering 286,000, will triple in the 1980s. The booklet begins with general information for the foreign student. Reference works providing information about U.S. colleges and universities and guides to financial planning and scholarship support are cited. The booklet then goes on to describe organizations and agencies which can provide students with general assistance and with assistance in particular fields of study. Also described are organizations administering foreign student exchange programs in the United States and foreign student services. The booklet concludes with a listing of U.S. embassies and other overseas posts, binational education foundations and commissions, and student counseling centers. (Author/RM)

A microfluidics-based three-dimensional skin-on-chip (SoC) model is developed in this study to enable quantitative studies of transendothelial and transepithelial migration of human T lymphocytes in mimicked skin inflammatory microenvironments and to test new drug candidates. The keys results include 1) CCL20-dependent T cell transmigration is significantly inhibited by an engineered CCL20 locked dimer (CCL20LD), supporting the potential immunotherapeutic use of CCL20LD for treating skin diseases such as psoriasis; 2) transepithelial migration of T cells in response to a CXCL12 gradient mimicking T cell egress from the skin is significantly reduced by a sphingosine-1-phosphate (S1P) background, suggesting the role of S1P for T cell retention in inflamed skin tissues; and 3) T cell transmigration is induced by inflammatory cytokine stimulated epithelial cells in the SoC model. Collectively, the developed SoC model recreates a dynamic multi-cellular micro-environment that enables quantitative studies of T cell transmigration at a single cell level in response to physiological cutaneous inflammatory mediators and potential drugs.

Degradation of extracellular Polyhydroxyalkanoates (PHAs) in the environment depends on the secretion of specific extracellular PHA depolymerases and lipases. Compared to extracellular scl-PHA degrading enzymes, extracellular enzymes that can degrade mcl-PHAs are poorly investigated. In this project, Proteobacteria members that produce extracellular mcl-PHAs depolymerases/ lipases were screened on mcl-PHA agar plates. Then, genes involved in the production and regulation of mcl-PHA depolymerases/lipases were identified using transposon mutagenesis, insertional mutagenesis, and bioinformatics prediction tools. Once the genes were identified, the mcl-PHA depolymerase/lipase encoding genes were cloned and characterized. Burkholderia thailandensis E264, Stenotrophomonas maltophilia K279a, S. maltophilia D457, and S. maltophilia NCPPB1683 were found to produce extracellular mcl-PHA depolymerases/lipases. In Pseudomonas chlororaphis PA23, transposon mutagenesis showed that disruption of certain metabolic pathways positively affects mcl-PHA depolymerase/lipase production. Transposon mutagenesis of B. cepacia ATCC 25416 indicated that disruption of the APZ15_13320 gene negatively affected the production of pigmented metabolites and positively affected mcl-PHA depolymerase/lipase production. A novel S. maltophilia strain that can produce mcl-PHA depolymerase/lipase was discovered during the screening process as a contaminant strain of the T. caryophylli DSMZ16666. Using whole-genome sequencing and bioinformatics, a putative extracellular mcl-PHA depolymerase/lipase known as fig|40323.255.peg.2780 was identified in the novel S. maltophilia HT01 strain. The in-silico prediction of a putative extracellular mcl-PHA depolymerase/lipase in S. maltophilia K279a resulted in twenty-five protein-coding sequences. Five of the twenty-five putative depolymerase/lipases were cloned in E. coli. The E. coli clones expressing these genes were screened for degradation of polyhydroxyoctanaoate

Oleaginous red yeasts are capable of producing an array of useful bioproducts including triacylglycerides (TAGs) for biodiesel and carotenoids for nutraceuticals. The previously under-characterized oleaginous red yeast, Rhodotorula diobovata, was the focus of this research. This study first examines the effect of aeration on R. diobovata grown under nitrogen-limiting conditions. Results showed a link between nitrogen-limitation and the onset of TAG synthesis, and a link between oxygen-limitation and the onset of carotenoid synthesis. To understand the molecular basis of these results, and R. diobovata’s productivity under varying culture conditions, the genome was sequenced, assembled, annotated and compared with other oleaginous yeasts in relation to their TAG and carotenoid biosynthesis. Amino acid sequence alignments of key proteins in the de novo fatty acid and carotenoid biosynthesis pathways revealed core differences between R. diobovata and other oleaginous non-carotenogenic yeasts such as Yarrowia lipolytica and Lipomyces starkeyi. A dot-plot analysis of the nucleotide sequences of key genes in the de novo fatty acid and carotenoid biosynthesis pathways revealed multiple inversions and frame shifts between the phenotypically similar R. graminis WP1 and R. diobovata. The availability of the annotated genome allowed for a robust proteomic investigation of R. diobovata conditions across growth phases under nitrogen- and oxygen- limiting conditions. Nitrogen- and oxygen-limitation across growth phases resulted in elevated levels of NADPH supplying proteins and downregulation of acetyl-CoA supplying proteins, which resulted in an overall reduction of fatty acid synthesis. The carotenoid biosynthetic pathways were however upregulated resulting in increased concentrations of carotenoids. This implies that the flux of acetyl-CoA favoured isoprenoid biosynthesis over fatty acid biosynthesis under nitrogen- and oxygen- limiting conditions across growth curve. Overall

Zinc oxide is used in the swine industry as an antibiotic-alternative, to protect piglets against Escherichia coli infections during the post-weaning period. The global overuse of zinc oxide in piglet feed is currently a major concern in the swine industry. The post-weaning period is a markedly sensitive period for piglets that is often characterized by illness, commonly diarrhea caused by enterotoxigenic E. coli (ETEC F4). There are several issues around the use of high doses of zinc oxide, of which environmental pollution is a major consideration. As a response to this concern, this research focuses on a targeted zinc oxide delivery approach by encapsulating zinc oxide in a physiologically active material. This preserves the antimicrobial activity of zinc oxide, while reducing overuse, and the mitigating the negative environmental impacts. Three zinc oxide encapsulated delivery vehicles were fabricated: ZnO-HET (whey protein, sodium alginate, and zinc oxide in a heterogenous mix); ZnO-SW (whey protein and sodium alginate shell encapsulating a zinc oxide core); and ZnO-L100 (commercial EUDRAGIT® L100 shell encapsulating a zinc oxide core). The zinc oxide release profiles were assessed under in vitro conditions, and in extracted digestive fluids. In both situations, ZnO-L100 demonstrated the most effective targeted delivery of zinc oxide to the intestinal environment, which is the area where ETEC F4 would physiologically colonize and infect in the post-weaning piglet. ZnO-L100 delivered at least 20% more zinc oxide to the intestinal environment compared to ZnO-HET and ZnO-SW (p < 0.05). As a result of this potential, it was of interest to investigate the antibacterial ability of ZnO-L100. Using the WST-8 microbial viability assay method, we demonstrated that ZnO-L100 had ETEC F4 antibacterial activity within 30 minutes and sustained antibacterial activity beyond 150 minutes. Overall, the ZnO-L100 product was able to demonstrate a responsive release profile favourabl

Immune cell migration plays an essential role in immune surveillance and homeostasis maintenance. Misguided migratory responses of immune cells contribute to various pathological issues. Understand ing the mechanisms of immune cell migration is crucial and its investigation requires a suitable approach. Although various methods for cell migration study have been established, most of them lacking configuration of the complex microenvironment in vitro which makes the development of a suitable approach of vital importance. Organ-on-chip (OoC) approach can provide a better platform due to its ability to simulate the key features of certain tissues or organs. In this thesis, we developed different OoC related approaches to study disease-oriented immune cell migration. Specifically, we employed clinical samples in microfluidic device to simulate the microenvironment of chronic obstructive pulmonary disease (COPD), and demonstrated the usage of this approach to quantitatively investigate the complex migratory responses of T cells in COPD. Our results showed an inhibitory effect of the COPD sputum on T cell motility and chemotaxis, which may suggest a possible stopping mechanism to facilitate T cell accumulati on in the airway in COPD. We also mimicked the tumor microenvironment in vitro using primary murine natural killer (NK) cells and mouse tumor cell line (i.e., 4T1) in our microfluidic device, and demonstrated it as a proof of principle approach to study di rectional NK cell migration and NK cancer cell interactions in real-time. Furthermore, we developed a mimicked skin-on-chip (SoC) model that configured the key features of human skin and relevant chemical fields during cutaneous inflammation, and demonstrated its feasibility as a versatile tool for investigating T cell migration and screening potential drugs for targeting chemotactic signaling. Collectively, studies in this thesis bridge organ-specific applications with disease-oriented immune cell migration, and ad

Background: The Value-Based Healthcare (VBH) concept is designed to improve individual healthcare outcomes without increasing expenditure, and is increasingly being used to determine resourcing of and reimbursement for medical services. Radiology is a major contributor to patient and societal healthcare at many levels. Despite this, some VBH models do not acknowledge radiology’s central role; this may have future negative consequences for resource allocation. Methods, findings and interpretation: This multi-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australia, and New Zealand, describes the place of radiology in VBH models and the health-care value contributions of radiology. Potential steps to objectify and quantify the value contributed by radiology to healthcare are outlined.

Given gridded cell-average data of a smooth multivariate function, we present a constructive explicit procedure for generating a high-order global approximation of the function. One contribution is the derivation of high order approximations to point-values of the function directly from the cell-average data. The second contribution is the development of univariate B-spline based high order quasi-interpolation operators using cell-average data. Multivariate spline quasi-interpolation approximation operators are obtained by tensor products of the univariate operators.

© 2017 Copyright held by the owner/author(s). The realistic simulation of highly-dynamic elastic objects is important for a broad range of applications in computer graphics, engineering and computational fabrication. However, whether simulating flipping toys, jumping robots, prosthetics or quickly moving creatures, performing such simulations in the presence of contact, impact and friction is both time consuming and inaccurate. In this paper we present Dynamics-Aware Coarsening (DAC) and the Boundary Balanced Impact (BBI) model which allow for the accurate simulation of dynamic, elastic objects undergoing both large scale deformation and frictional contact, at rates up to 79 times faster than state-of-the-art methods. DAC and BBI produce simulations that are accurate and fast enough to be used (for the first time) for the computational design of 3D-printable compliant dynamic mechanisms. Thus we demonstrate the efficacy of DAC and BBI by designing and fabricating mechanisms which flip, throw and jump over and onto obstacles as requested.

Active structures have the ability to change their shape, properties, and functionality as a response to changing operational conditions, which makes them more versatile than their static counterparts. However, most active structures currently lack the capability to achieve multiple, different target states with a single input actuation or require a tedious material programming step. Furthermore, the systematic design and fabrication of active structures is still a challenge as many structures are designed by hand in a trial and error process and thus are limited by engineers' knowledge and experience. In this work, a computational design and fabrication framework is proposed to generate structures with multiple target states for one input actuation that don't require a separate training step. A material dithering scheme based on multi-material 3D printing is combined with locally applied copper coil heating elements and sequential heating patterns to control the thermo-mechanical properties of the structures and switch between the different deformation modes. A novel topology optimization approach based on power diagrams is used to encode the different target states in the structure while ensuring the fabricability of the structures and the compatibility with the drop-in heating elements. The versatility of the proposed framework is demonstrated for four different example structures from engineering and computer graphics. The numerical and experimental results show that the optimization framework can produce structures that show the desired motion, but experimental accuracy is limited by current fabrication methods. The generality of the proposed method makes it suitable for the development of structures for applications in many different fields from aerospace to robotics to animated fabrication in computer graphics.

We present a new method for computing a smooth minimum distance function based on the LogSumExp function for point clouds, edge meshes, triangle meshes, and combinations of all three. We derive blending weights and a modified Barnes-Hut acceleration approach that ensure our method approximates the true distance, and is conservative (points outside the zero isosurface are guaranteed to be outside the surface) and efficient to evaluate for all the above data types. This, in combination with its ability to smooth sparsely sampled and noisy data, like point clouds, shortens the gap between data acquisition and simulation, and thereby enables new applications such as direct, co-dimensional rigid body simulation using unprocessed lidar data., Comment: 17 pages, 23 figures

We present a new approach for modelling musculoskeletal anatomy. Unlike previous methods, we do not model individual muscle shapes as geometric primitives (polygonal meshes, NURBS etc.). Instead, we adopt a volumetric segmentation approach where every point in our volume is assigned to a muscle, fat, or bone tissue. We provide an interactive modelling tool where the user controls the segmentation via muscle curves and we visualize the muscle shapes using volumetric rendering. Muscle curves enable intuitive yet powerful control over the muscle shapes. This representation allows us to automatically handle intersections between different tissues (musclemuscle, muscle-bone, and muscle-skin) during the modelling and automates computation of muscle fiber fields. We further introduce a novel algorithm for converting the volumetric muscle representation into tetrahedral or surface geometry for use in downstream tasks. Additionally, we introduce an interactive skeleton authoring tool that allows the users to create skeletal anatomy starting from only a skin mesh using a library of bone parts., Comment: 13 pages, 20 figures, SIGGRAPH 2021

We consider a problem of great practical interest: the repairing and recovery of a low-dimensional manifold embedded in high-dimensional space from noisy scattered data. Suppose that we observe a point cloud sampled from the low-dimensional manifold, with noise, and let us assume that there are holes in the data. Can we recover missing information inside the holes? While in low-dimension the problem was extensively studied, manifold repairing in high dimension is still an open problem. We introduce a new approach, called Repairing Manifold Locally Optimal Projection (R-MLOP), that expands the MLOP method introduced by Faigenbaum-Golovin et al. in 2020, to cope with manifold repairing in low and high-dimensional cases. The proposed method can deal with multiple holes in a manifold. We prove the validity of the proposed method, and demonstrate the effectiveness of our approach by considering different manifold topologies, for single and multiple holes repairing, in low and high dimensions., Comment: arXiv admin note: text overlap with arXiv:2012.13804, arXiv:2012.12546

Stress is a normal part of life for fungi, which can survive in environments considered inhospitable or hostile for other organisms. Due to the ability of fungi to respond to, survive in, and transform the environment, even under severe stresses, many researchers are exploring the mechanisms that enable fungi to adapt to stress. The International Symposium on Fungal Stress (ISFUS) brings together leading scientists from around the world who research fungal stress. This article discusses presentations given at the third ISFUS, held in São José dos Campos, São Paulo, Brazil in 2019, thereby summarizing the state-of-the-art knowledge on fungal stress, a field that includes microbiology, agriculture, ecology, biotechnology, medicine, and astrobiology.

The main objectives of this study were to numerically model negative air ionization for removal of bioaerosols and, to experimentally determine the effects of air ionization on the concentrations and the infectivity of aerosolized virus in enclosed spaces without ventilation. The Finite Volume Method (FVM) was used to simulate the physical processes of bioaerosol removal from air. A commercial software package (ANSYS FLUENT) was used to implement the FVM model. The transport of bioaerosols were modeled as a discrete phase using the Lagrangian approach under discrete random walk. The ions were modelled as unipolar (negatively charged) with a constant generation rate into the confined space. Experiments were conducted using a commercial ionizer in a chamber to validate the model and to quantify the effects of ionization on viral infectivity and virion (viral particles) concentrations. The model predictions of bioaerosol removal were within 22% of the measured values. The results showed that at a steady-state ion concentration of 2.4 E13 ions/m³ , ionization significantly reduced the concentrations of bioaerosols over time. The reduction of bioaerosol concentrations led to a one log10 reduction in virion concentrations over 90 s of ionization. Furthermore, at a steady-state ion concentration of 2.4 E13 ions/m³, ionization began to cause a significant reduction in viral infectivity at 30 s of ionization until a two log10 reduction in viral infectivity was achieved at 90 s. However, at a steady state ion concentration of 3.0 E10 ions/m³, ionization did not produce any significant effect on the viral infectivity. In conclusion, ionization is an effective technology for the purification of air in enclosed spaces when a critical ion threshold is present. The model presented in this study can be used as a tool to predict the spread and removal of bioaerosols in enclosed spaces.

Among different types of thermoplastics, polyhydroxyalkanoates (PHAs) with different physical/mechanical and thermal properties are well known, as they are biodegradable, biocompatible, and non-toxic. However, the main drawback of PHA biosynthesis in large scale is the high cost of production. It is known that PHA production can be considerably increased under oxygen-limited conditions. In this study, growth and synthesis of medium chain length PHAs (mcl-PHAs) by Pseudomonas putida LS46 cultured with octanoic acid under oxygen-limited conditions in the batch mode was modeled. Four models including the Monod model incorporated Leudeking–Piret (MLP), the Moser model incorporated Leudeking–Piret (Moser-LP), the Logistic model incorporated Leudeking–Piret (LLP), and the Modified Logistic model incorporated Leudeking–Piret (MLLP) were investigated. Kinetic parameters of each model were calibrated by using the multi-objective optimization algorithm, Pareto Archived Dynamically Dimensioned Search (PA-DDS) by minimizing the sum of absolute error (SAE) for PHA production and growth simultaneously. Among the four models, MLP and Moser-LP models adequately represented the experimental data for oxygen limited conditions. In addition, the MLP and Moser-LP models could not adequately simulate PHA production under oxygen excess conditions. For growth, under oxygen excess conditions, this deviation was not very significant.

Thin-layer drying characteristics of fresh and partially field-dried buckwheat hay were studied at 30 to 180 °C drying temperatures, 12.5 to 60% relative humidities and 0.2 m s-1 constant airflow. The hay was harvested three different times with a 10 to 12 days interval between the harvesting times. Three-fourth of the harvested hay was sun-dried on the field for 4 days (referred to as partially field-dried hay). The drying behaviour of different parts of the hay (flowers, leaves and stems) was tested separately. During drying, the hay samples’ mass was measured at intervals of 60 to 900 s. These measurements were used to characterize the drying behaviour of fresh or partially field-dried hay, which include: mass ratios, drying constants, effective water diffusivities and activation energies. Non-linear regression analysis was conducted using semi-theoretical or empirical models. A constant-rate period of drying for different parts of both fresh and partial field-dried hay was not observed. These distinctive parts required varying drying times to reach their EMC. The order of the drying time from fastest to slowest, is: flowers, leaves, then stems. Partially field-dried and/or later harvested hay needed less drying time. Because of its highest R2 and the lowest MSE, the logarithmic model was the best fit model for all of the tested drying and harvest conditions. Optimum harvesting time was about 70 days after sowing. The hay’s effective moisture diffusivity ranged between 10-12 to 10-9 m2 s-1; the activation energy of the hay ranged between 19.63 to 37.42 kJ mol-1. The determined drying characteristics of fresh and field-dried hay would be useful in designing of commercial drying system for buckwheat hay.

EMU is an efficient and scalable model to simulate bulk musculoskeletal motion with heterogenous materials. First, EMU requires no model reductions, or geometric coarsening, thereby producing results visually accurate when compared to an FEM simulation. Second, EMU is efficient and scales much better than state-of-the-art FEM with the number of elements in the mesh, and is more easily parallelizable. Third, EMU can handle heterogeneously stiff meshes with an arbitrary constitutive model, thus allowing it to simulate soft muscles, stiff tendons and even stiffer bones all within one unified system. These three key characteristics of EMU enable us to efficiently orchestrate muscle activated skeletal movements. We demonstrate the efficacy of our approach via a number of examples with tendons, muscles, bones and joints.

We propose a novel algorithm to efficiently generate hidden structures to support arrangements of floating rigid objects. Our optimization finds a small set of rods and wires between objects and each other or a supporting surface (e.g., wall or ceiling) that hold all objects in force and torque equilibrium. Our objective function includes a sparsity inducing total volume term and a linear visibility term based on efficiently pre-computed Monte-Carlo integration, to encourage solutions that are as-hidden-as-possible. The resulting optimization is convex and the global optimum can be efficiently recovered via a linear program. Our representation allows for a user-controllable mixture of tension-, compression-, and shear-resistant rods or tension-only wires. We explore applications to theatre set design, museum exhibit curation, and other artistic endeavours.

In this technical report, we investigate efficient representations of articulated objects (e.g. human bodies), which is an important problem in computer vision and graphics. To deform articulated geometry, existing approaches represent objects as meshes and deform them using "skinning" techniques. The skinning operation allows a wide range of deformations to be achieved with a small number of control parameters. This paper introduces a method to invert the deformations undergone via traditional skinning techniques via a neural network parameterized by pose. The ability to invert these deformations allows values (e.g., distance function, signed distance function, occupancy) to be pre-computed at rest pose, and then efficiently queried when the character is deformed. We leave empirical evaluation of our approach to future work.

In some applications, one is interested in reconstructing a function $f$ from its Fourier series coefficients. The problem is that the Fourier series is slowly convergent if the function is non-periodic, or is non-smooth. In this paper, we suggest a method for deriving high order approximation to $f$ using a Pad\'e-like method. Namely, by fitting some Fourier coefficients of the approximant to the given Fourier coefficients of $f$. Given the Fourier series coefficients of a function on a rectangular domain in $\mathbb{R}^d$, assuming the function is piecewise smooth, we approximate the function by piecewise high order spline functions. First, the singularity structure of the function is identified. For example in the 2-D case, we find high accuracy approximation to the curves separating between smooth segments of $f$. Secondly, simultaneously we find the approximations of all the different segments of $f$. We start by developing and demonstrating a high accuracy algorithm for the 1-D case, and we use this algorithm to step up to the multidimensional case., Comment: 22 pages, 21 figures

In this paper, we present a method for denoising and reconstruction of low-dimensional manifold in high-dimensional space. We suggest a multidimensional extension of the Locally Optimal Projection algorithm which was introduced by Lipman et al. in 2007 for surface reconstruction in 3D. The method bypasses the curse of dimensionality and avoids the need for carrying out dimensional reduction. It is based on a non-convex optimization problem, which leverages a generalization of the outlier robust L1-median to higher dimensions while generating noise-free quasi-uniformly distributed points reconstructing the unknown low-dimensional manifold. We develop a new algorithm and prove that it converges to a local stationary solution with a bounded linear rate of convergence in case the starting point is close enough to the local minimum. In addition, we show that its approximation order is $O(h^2)$, where $h$ is the representative distance between the given points. We demonstrate the effectiveness of our approach by considering different manifold topologies with various amounts of noise, including a case of a manifold of different co-dimensions at different locations.

In this paper, we consider the fundamental problem of approximation of functions on a low-dimensional manifold embedded in a high-dimensional space, with noise affecting both in the data and values of the functions. Due to the curse of dimensionality, as well as to the presence of noise, the classical approximation methods applicable in low dimensions are less effective in the high-dimensional case. We propose a new approximation method that leverages the advantages of the Manifold Locally Optimal Projection (MLOP) method (introduced by Faigenbaum-Golovin and Levin in 2020) and the strengths of the method of Radial Basis Functions (RBF). The method is parametrization free, requires no knowledge regarding the manifold's intrinsic dimension, can handle noise and outliers in both the function values and in the location of the data, and is applied directly in the high dimensions. We show that the complexity of the method is linear in the dimension of the manifold and squared-logarithmic in the dimension of the codomain of the function. Subsequently, we demonstrate the effectiveness of our approach by considering different manifold topologies and show the robustness of the method to various noise levels., Comment: arXiv admin note: text overlap with arXiv:2012.12546

Linear approximation approaches suffer from Gibbs oscillations when approximating functions with singularities. ENO-SR resolution is a local approach avoiding oscillations and with a full order of accuracy, but a loss of regularity of the approximant appears. The goal of this paper is to introduce a new approach having both properties of full accuracy and regularity. In order to obtain it, we propose a three-stage algorithm: first, the data is smoothed by subtracting an appropriate non-smooth data sequence; then a chosen high order linear approximation operator is applied to the smoothed data and finally, an approximation with the proper singularity structure is reinstated by correcting the smooth approximation with the non-smooth element used in the first stage. We apply this approach to both cases of point-value data and of cell-average data, using the 4-point subdivision algorithm in the second stage. Using the proposed approach we are able to construct approximations with high precision, with high piecewise regularity, and without diffusion nor oscillations in the presence of discontinuities., Comment: 33 pages