-
3D Printing in Medicine Apr 2020Fill density is a critical parameter affecting the functional performance of 3D printed porous constructs in the biomedical and pharmaceutical domain. Numerous studies...
Understanding the relationship between slicing and measured fill density in material extrusion 3D printing towards precision porosity constructs for biomedical and pharmaceutical applications.
BACKGROUND
Fill density is a critical parameter affecting the functional performance of 3D printed porous constructs in the biomedical and pharmaceutical domain. Numerous studies have reported the impact of fill density on the mechanical properties, diffusion characteristics and content release rates of constructs. However, due to the way in which slicing toolpath calculations are performed, there is substantial deviation between the measured and slicing fill density for relatively small sized constructs printed at low fill densities (high porosities). The purpose of the current study was to investigate this discrepancy using a combination of mathematical modeling and experimental validation.
METHODS
The open source slicer Slic3r was used to 3D print 20 mm × 20 mm × 5 mm constructs at three identified slicing fill density values, 9.58%, 20.36% and 32.33% (exact values entered into software), in triplicates. A mathematical model was proposed to accurately predict fill density, and the measured fill density was compared to both the predicted as well as the slicing fill density. The model was further validated at two additional slicing fill densities of 15% and 40%. The total material within the construct was analyzed from the perspective of material extruded within the beads as well as the bead to bead interconnects using the predictive model.
RESULTS
The slicing fill density deviated substantially from measured fill density at low fill densities with absolute errors larger than 26% in certain instances. The proposed model was able to predict fill density to within 5% of the measured fill density in all cases. The average absolute error between predicted vs. measured fill density was 3.5%, whereas that between slicing vs. measured fill density was 13%. The material extruded in the beads varied from 86.5% to 95.9%, whereas that extruded in the interconnects varied from 13.5% to 4.1%.
CONCLUSIONS
The proposed model and approach was able to predict fill density to a reasonable degree of accuracy. Findings from the study could prove useful in applications where controlling construct fill density in relatively small sized constructs is important for achieving targeted levels of functional criteria such as mechanical strength, weight loss and content release rate.
PubMed: 32335739
DOI: 10.1186/s41205-020-00063-8 -
Nanomaterials (Basel, Switzerland) Jun 2023Having access to accurate electron densities in chemical systems, especially for dynamical systems involving chemical reactions, ion transport, and other charge transfer...
Having access to accurate electron densities in chemical systems, especially for dynamical systems involving chemical reactions, ion transport, and other charge transfer processes, is crucial for numerous applications in materials chemistry. Traditional methods for computationally predicting electron density data for such systems include quantum mechanical (QM) techniques, such as density functional theory. However, poor scaling of these QM methods restricts their use to relatively small system sizes and short dynamic time scales. To overcome this limitation, we have developed a deep neural network machine learning formalism, which we call deep charge density prediction (DeepCDP), for predicting charge densities by only using atomic positions for molecules and condensed phase (periodic) systems. Our method uses the weighted smooth overlap of atomic positions to fingerprint environments on a grid-point basis and map it to electron density data generated from QM simulations. We trained models for bulk systems of copper, LiF, and silicon; for a molecular system, water; and for two-dimensional charged and uncharged systems, hydroxyl-functionalized graphane, with and without an added proton. We showed that DeepCDP achieves prediction R2 values greater than 0.99 and mean squared error values on the order of 10-5e2 Å-6 for most systems. DeepCDP scales linearly with system size, is highly parallelizable, and is capable of accurately predicting the excess charge in protonated hydroxyl-functionalized graphane. We demonstrate how DeepCDP can be used to accurately track the location of charges (protons) by computing electron densities at a few selected grid points in the materials, thus significantly reducing the computational cost. We also show that our models can be transferable, allowing prediction of electron densities for systems on which it has not been trained but that contain a subset of atomic species on which it has been trained. Our approach can be used to develop models that span different chemical systems and train them for the study of large-scale charge transport and chemical reactions.
PubMed: 37368284
DOI: 10.3390/nano13121853 -
Research in Number Theory 2023The geometric sieve for densities is a very convenient tool proposed by Poonen and Stoll (and independently by Ekedahl) to compute the density of a given subset of the...
The geometric sieve for densities is a very convenient tool proposed by Poonen and Stoll (and independently by Ekedahl) to compute the density of a given subset of the integers. In this paper we provide an effective criterion to find all higher moments of the density (e.g. the mean, the variance) of a subset of a finite dimensional free module over the ring of algebraic integers of a number field. More precisely, we provide a geometric sieve that allows the computation of all higher moments corresponding to the density, over a general number field . This work advances the understanding of geometric sieve for density computations in two ways: on one hand, it extends a result of Bright, Browning and Loughran, where they provide the geometric sieve for densities over number fields; on the other hand, it extends the recent result on a geometric sieve for expected values over the integers to both the ring of algebraic integers and to moments higher than the expected value. To show how effective and applicable our method is, we compute the density, mean and variance of Eisenstein polynomials and shifted Eisenstein polynomials over number fields. This extends (and fully covers) results in the literature that were obtained with ad-hoc methods.
PubMed: 37546177
DOI: 10.1007/s40993-023-00466-6 -
PloS One 2020Recent research shows significant economic benefit if the processing sweet corn [Zea mays L. var. rugosa (or saccharata)] industry grew crowding stress tolerant (CST)...
Recent research shows significant economic benefit if the processing sweet corn [Zea mays L. var. rugosa (or saccharata)] industry grew crowding stress tolerant (CST) hybrids at their optimum plant densities, which may exceed current plant densities by up to 14,500 plants ha-1. However, optimum plant density of individual fields varies over years and across the Upper Midwest (Illinois, Minnesota and Wisconsin), where processing sweet corn is concentrated. The objectives of this study were to: (1) determine the extent to which environmental and management practices affect optimum plant density and, (2) identify the most appropriate recommendation domain for making decisions on plant density. To capture spatial and temporal variability in optimum plant density, on-farm experiments were conducted at thirty fields across the states of Illinois, Minnesota and Wisconsin, from 2013 to 2017. Exploratory factor analysis of twelve environmental and management variables revealed two factors, one related to growing period and the other defining soil type, which explained the maximum variability observed across all the fields. These factors were then used to quantify the strength of associations with optimum plant density. Pearson's partial correlation coefficients of 'growing period' and 'soil type' with optimum plant density were low (ρ1 = -0.14 and ρ2 = -0.09, respectively) and non-significant (P = 0.47 and 0.65, respectively). To address the second objective, six candidate recommendation domain models (RDM) were developed and tested. Linear mixed effects models describing crop response to plant density were fit to each level of each candidate RDM. The difference in profitability observed at the current plant density for a field and the optimum plant density under RDM level represented the additional processor profit ($ ha-1) from a field. The RDM built around 'Production Area' (RDMPA) appears most suitable, because plant density recommendations based on RDMPA maximized processor profits as well grower returns better than other RDMs. Compared to current plant density, processor profits and grower returns increased by $448 ha-1 and $82 ha-1, respectively at plant densities under RDMPA.
Topics: Agriculture; Population Density; Soil; Stress, Physiological; Zea mays
PubMed: 32032371
DOI: 10.1371/journal.pone.0228809 -
Journal of Clinical and Experimental... Dec 2022Knowledge of bone density in maxilla and mandible will allow the clinician to plan the anchorage strategies and placement of implants with necessary precautions. The...
BACKGROUND
Knowledge of bone density in maxilla and mandible will allow the clinician to plan the anchorage strategies and placement of implants with necessary precautions. The study aims to evaluate the deflection changes of titanium alloy self-drilling mini implants from the intended path that occurs during placement in varying bone densities.
MATERIAL AND METHODS
63 titanium alloy self-drilling mini implants of the lengths 6mm, 8mm, and 10mm with diameter of 1.3mm were placed in three homogenous solid rigid polyurethane foam (saw bone) with bone densities of 20pcf, 30pcf, and 40pcf simulating anatomic sites in maxilla and mandible. 7mini implants of each length in all bone densities were tested for study. The implants were inserted perpendicularly into artificial bone block held in a custom made stand. The bone blocks were then radiographically exposed and the deviation of the long axis of the implantfrom a true vertical line was measured.
RESULTS
There was a decrease in deflection of the mini implant with increase in density. On the other hand, increase in length resulted in increase in the amount of deflection.
CONCLUSIONS
Longer mini implants can be used in less dense bone as in maxilla, whereas shorter mini implants can be used in high dense bone as in mandible to increase the stability and success rate of implants. Bone density and implant length play a role in deflection of mini implant from its intended path of insertion. Orthodontic Mini implants, deflection, bone density, anchorage.
PubMed: 36601239
DOI: 10.4317/jced.59903 -
Ecological Applications : a Publication... Jan 2021Over the past two decades, there have been numerous calls to make ecology a more predictive science through direct empirical assessments of ecological models and...
Over the past two decades, there have been numerous calls to make ecology a more predictive science through direct empirical assessments of ecological models and predictions. While the widespread use of model selection using information criteria has pushed ecology toward placing a higher emphasis on prediction, few attempts have been made to validate the ability of information criteria to correctly identify the most parsimonious model with the greatest predictive accuracy. Here, we used an ecological forecasting framework to test the ability of information criteria to accurately predict the relative contribution of density dependence and density-independent factors (forage availability, harvest, weather, wolf [Canis lupus] density) on inter-annual fluctuations in beaver (Castor canadensis) colony densities. We modeled changes in colony densities using a discrete-time Gompertz model, and assessed the performance of four models using information criteria values: density-independent models with (1) and without (2) environmental covariates; and density-dependent models with (3) and without (4) environmental covariates. We then evaluated the forecasting accuracy of each model by withholding the final one-third of observations from each population and compared observed vs. predicted densities. Information criteria and our forecasting accuracy metrics both provided strong evidence of compensatory density dependence in the annual dynamics of beaver colony densities. However, despite strong within-sample performance by the most complex model (density-dependent with covariates) as determined using information criteria, hindcasts of colony densities revealed that the much simpler density-dependent model without covariates performed nearly as well predicting out-of-sample colony densities. The hindcast results indicated that the complex model over-fit our data, suggesting that parameters identified by information criteria as important predictor variables are only marginally valuable for predicting landscape-scale beaver colony dynamics. Our study demonstrates the importance of evaluating ecological models and predictions with long-term data and revealed how a known limitation of information criteria (over-fitting of complex models) can affect our interpretation of ecological dynamics. While incorporating knowledge of the factors that influence animal population dynamics can improve population forecasts, we suggest that comparing forecast performance metrics can likewise improve our knowledge of the factors driving population dynamics.
Topics: Animals; Forecasting; Population Dynamics; Rodentia; Weather; Wolves
PubMed: 32583507
DOI: 10.1002/eap.2198 -
Animals : An Open Access Journal From... Aug 2021The study aimed to compare the growth performance and physiological responses of bester (B) and backcrossed bester ♀ × beluga ♂ (BB) in response to crowding stress...
The study aimed to compare the growth performance and physiological responses of bester (B) and backcrossed bester ♀ × beluga ♂ (BB) in response to crowding stress under different stocking densities, as well as to establish a threshold stocking density for rearing BB in a recirculating aquaculture system (RAS) without welfare impairment. For this purpose, in the first trial (T1), B (181.15 ± 21.21 g) and BB fingerlings (181.98 ± 28.65 g) were reared in two stocking densities of 2 kg/m and 4 kg/m in fiberglass tanks (1 m) for 6 weeks. In a parallel trial (T2), the BB hybrids (335.24 ± 39.30 g) were kept in four initial stocking densities, ranging from 5 kg/m to 12 kg/m. The results of T1 revealed better growth indices (i.e., final mean weight, weight gain, specific growth rate) at lower stocking densities for both hybrids; however, in terms of growth performance, the BB hybrid showed better results when compared with the B hybrid. BB hybrids registered significantly ( < 0.05) lower serum cortisol and MDA and higher lysozyme than B hybrids, showing higher tolerance to crowding stress. Nevertheless, at higher densities, selected serum parameters (i.e., hematological indices, cortisol, glucose, protein, malondialdehyde, lysozyme) and growth performance indices used to evaluate the hybrids indicate that high stocking density could affect the growth and welfare of BB hybrids, and that the selected serum parameters could be used as good indicators for chronic stress caused by overcrowding conditions.
PubMed: 34438750
DOI: 10.3390/ani11082292 -
Biology May 2022With laboratory zebrafish () being an established and popular research model, there is a need for universal, research-based husbandry guidelines for this species, since...
With laboratory zebrafish () being an established and popular research model, there is a need for universal, research-based husbandry guidelines for this species, since guidelines can help promote good welfare through providing appropriate care. Despite the widespread use of zebrafish in research, it remains unclear how holding densities affect their welfare. Previous studies have mainly evaluated the effects of holding densities on a single parameter, such as growth, reproductive output, or social interactions, rather than looking at multiple welfare parameters simultaneously. Here we investigated how chronic (nine weeks) exposure to five different holding densities (1, 4, 8, 12, and 16 fish/L) affected multiple welfare indicators. We found that fish in the 1 fish/L density treatment had higher free water cortisol concentrations per fish, increased vertical distribution, and displayed aggressive behaviour more frequently than fish held at higher densities. On the other hand, density treatments had no effect on anxiety behaviour, whole-brain neurotransmitter levels, egg volume, or the proportion of fertilised eggs. Our results demonstrate that zebrafish can be held at densities between 4 and 16 fish/L without compromising their welfare. However, housing zebrafish in the density of 1 fish/L increased their stress level and aggressive behaviour.
PubMed: 35625453
DOI: 10.3390/biology11050725 -
Molecular Pharmaceutics Apr 2010This study was undertaken to examine the influence of seeding density, extracellular matrix and days in culture on bile acid transport proteins and hepatobiliary...
This study was undertaken to examine the influence of seeding density, extracellular matrix and days in culture on bile acid transport proteins and hepatobiliary disposition of the model bile acid taurocholate. Mouse hepatocytes were cultured in a sandwich configuration on six-well Biocoat plates with an overlay of Matrigel (BC/MG) or gelled-collagen (BC/GC) for 3 or 4 days at seeding densities of 1.0, 1.25, or 1.5 x 10(6) cells/well. The lower seeding densities of 1.0 and 1.25 x 10(6) cells/well resulted in good hepatocyte morphology and bile canalicular network formation, as visualized by 5-(and 6)-carboxy-2',7'-dichlorofluorescein accumulation. In general, taurocholate cellular accumulation tended to increase as a function of seeding density in BC/GC; cellular accumulation was significantly increased in hepatocytes cultured in BC/MG compared to BC/GC at the same seeding density on both days 3 and 4 of culture. In general, in vitro intrinsic biliary clearance of taurocholate was increased at higher seeding densities. Levels of bile acid transport proteins on days 3 and 4 were not markedly influenced by seeding density or extracellular matrix except for multidrug resistance protein 4 (Mrp4), which was inversely related to seeding density. Mrp4 levels decreased approximately 2- to 3-fold between seeding densities of 1.0 x 10(6) and 1.25 x 10(6) cells/well regardless of extracellular matrix; an additional approximately 3- to 5-fold decrease in Mrp4 protein was noted in BC/GC between seeding densities of 1.25 x 10(6) and 1.5 x 10(6) cells/well. Results suggest that seeding density, extracellular matrix and days in culture profoundly influence Mrp4 expression in sandwich-cultured mouse hepatocytes. Primary mouse hepatocytes seeded in a BC/MG configuration at densities of 1.25 x 10(6) cells/well and 1.0 x 10(6), and cultured for 3 days, yielded optimal transport based on the probes studied. This work demonstrates the applicability of the sandwich-cultured model to mouse hepatocytes.
Topics: Animals; Bile Acids and Salts; Biological Transport; Cells, Cultured; Extracellular Matrix; Hepatocytes; Immunoblotting; Male; Mice; Mice, Inbred C57BL; Multidrug Resistance-Associated Proteins; Taurocholic Acid
PubMed: 19968322
DOI: 10.1021/mp900227a -
PloS One 2012Restriction of behavioral opportunities and uneven use of space are considerable welfare concerns in modern broiler production, particularly when birds are kept at high...
Restriction of behavioral opportunities and uneven use of space are considerable welfare concerns in modern broiler production, particularly when birds are kept at high densities. We hypothesized that increased environmental complexity by provision of barrier perches would help address these issues by encouraging perching and enhancing use of the pen space across a range of stocking densities. 2,088 day-old broiler chicks were randomly assigned to one of the following barrier and density treatment combinations over four replications: simple barrier, complex barrier, or control (no barrier) and low (8 birds/m(2)), moderate (13 birds/m(2)), or high (18 birds/m(2)) density. Data were collected on focal birds via instantaneous scan sampling from 2 to 6 weeks of age. Mean estimates per pen for percent of observations seen performing each behavior, as well as percent of observations in the pen periphery vs. center, were quantified and submitted to an analysis of variance with week as the repeated measure. Barrier perches, density and age affected the behavioral time budget of broilers. Both simple and complex barrier perches effectively stimulated high perching rates. Aggression and disturbances were lower in both barrier treatments compared to controls (P<0.05). Increasing density to 18 birds/m(2) compared to the lower densities suppressed activity levels, with lower foraging (P<0.005), decreased perching (P<0.0001) and increased sitting (P = 0.001) earlier in the rearing period. Disturbances also increased at higher densities (P<0.05). Use of the central pen area was higher in simple barrier pens compared to controls (P<0.001), while increasing density above 8 birds/m(2) suppressed use of the central space (P<0.05). This work confirms some negative effects of increasing density and suggests that barrier perches have the potential to improve broiler welfare by encouraging activity (notably by providing accessible opportunities to perch), decreasing aggression and disturbances, and promoting more even distribution of birds throughout the pen space.
Topics: Age Factors; Aggression; Animals; Appetitive Behavior; Architectural Accessibility; Behavior, Animal; Chickens; Environment; Housing, Animal; Motor Activity; Population Density; Spatial Behavior
PubMed: 22299026
DOI: 10.1371/journal.pone.0029826