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This paper introduces a new concept of Caputo type interval-valued fractional conformable calculus. Based on this, some theorems and properties related to fractional conformable calculus are presented. As an application, this paper attempts to investigate an initial value problem of functional integro-differential equations with Caputo type interval-valued fractional conformable derivatives. We not only prove the existence of at least one solution, the extremal solutions and the unique solution of the above problem, but also establish some monotone iterative sequences converging to the extremal solutions. More meaningful and important, some comparison principles and generalized Gronwall inequality related to the proposed problem are also proved. Two examples are presented to illustrate the main results. We firmly believe that the concept of interval-valued fractional conformable calculus, new comparison principles and generalized Gronwall inequality introduced here can be conveniently applied to qualitative analysis of a variety of new interval-valued fractional conformable biological models, economic models, etc., which will better describe and explain various complex phenomena derived from the real world. [ABSTRACT FROM AUTHOR]

Each week, I record audio summaries for every paper in JACC, as well as an issue summary. Although this process is quite time-consuming, I have become familiar with every paper that we publish. Thus, I have personally selected the top 100 papers (both Original Investigations and Review Articles) from the distinct specialties each year. In addition to my personal choices, I have included papers that have been the most accessed or downloaded on our websites, as well as those selected by the JACC Editorial Board members. In order to present the full breadth of this important research in a consumable fashion, we will present these abstracts in this issue of JACC, as well as their Central Illustrations. The highlights comprise the following sections: Basic & Translational Research, Cardiac Failure & Myocarditis, Cardiomyopathies & Genetics, Cardio-Oncology, Congenital Heart Disease, Coronary Disease & Interventions, Coronavirus (as a NEW section), Hypertension, Imaging, Metabolic & Lipid Disorders, Neurovascular Disease & Dementia, Promoting Health & Prevention, Rhythm Disorders & Thromboembolism, Valvular Heart Disease, and Vascular Medicine (1-100). [ABSTRACT FROM AUTHOR]

• In this paper, an improved clustering method based on biological principles is presented. • The approach incorporates two new mechanism for improving the performance of the original Cellular Clustering Algorithm. • The first mechanism is a pre-processing approach for reducing the dataset dimensionality. • The second process includes an optimization method to automatically find the best data resolution. A clustering methodology based on biological visual models that imitates how humans visually cluster data by spatially associating patterns has been recently proposed. The method is based on Cellular Neural Networks and some resolution adjustments. The Cellular Neural Network rebuilds low-density areas while different resolutions find the best clustering option. The algorithm has demonstrated good performance compared to other clustering techniques. However, its main drawbacks correspond to its inability to operate with more than two-dimensional data sets and the computational time required for the resolution adjustment mechanism. This paper proposes a new version of this clustering methodology to solve such flaws. In the new approach, a pre-processing stage is incorporated featuring a Self-Organization Map that maps complex high-dimensional relations into a reduced lattice yet preserving the topological organization of the initial data set. This reduced representation is employed as the two-dimensional data set for further processing. In the new version, the resolution adjustment process is also accelerated through the use of an optimization method that combines the Hill-Climbing and the Random Search techniques. By incorporating such mechanisms rather than evaluating all possible resolutions, the optimization strategy finds the best resolution for a clustering problem by using a limited number of iterations. The proposed approach has been evaluated, considering several two-dimensional and high-dimensional datasets. Experimental evidence exhibits that the proposed algorithm performs the clustering task over complex problems delivering a 46% faster on average than the original method. The approach is also compared to other popular clustering techniques reported in the literature. Computational experiments demonstrate competitive results in comparison to other algorithms in terms of accuracy and robustness. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with a reaction-diffusion model incorporating delay and nonlocal effects. The normal form of double Hopf bifurcation is derived. The diffusive model of pollen tube tip growth is discussed and numerical simulations show that spatially homogeneous and inhomogeneous periodic solutions can be both stable or connected by a heteroclinic orbit under certain conditions. In addition, the diffusive Lotka-Volterra model with delay and nonlocality is considered and spatially inhomogeneous quasi-periodic solution is obtained. • Derive the algorithm of normal form of double Hopf bifurcation for reaction-diffusion system with delay and spatial average. • Investigate the dynamics near the double Hopf bifurcation point for two biological models. • Find bistability of homogeneous and inhomogeneous periodic solutions and pattern transitions for pollen tube tip growth model. • Find stable inhomogeneous quasi-periodic solutions and pattern transitions of periodic and quasi-periodic solutions for Lotka-Volterra model. [ABSTRACT FROM AUTHOR]

As a scientific discipline, systems biology aims to build models of biological systems and processes through the computer analysis of a large amount of experimental data describing the behaviour of whole cells. It is within this context that we already developed the Biomolecular Network Ontology especially for the semantic understanding of the behaviour of complex biomolecular networks and their transittability. However, the challenge now is how to automatically populate it from a variety of biological documents. To this end, the target of this paper is to propose a new approach to automatically populate the Biomolecular Network Ontology and take advantage of the vast amount of biological knowledge expressed in heterogeneous unstructured data about complex biomolecular networks. Indeed, we have recently observed the emergence of deep learning techniques that provide significant and rapid progress in several domains, particularly in the process of deriving high-quality information from text. Despite its significant progress in recent years, deep learning is still not commonly used to populate ontologies. In this paper, we present a deep learning-based NLP ontology population system to populate the Biomolecular Network Ontology. Its originality is to jointly exploit deep learning and natural language processing techniques to identify, extract and classify new instances referring to the BNO ontology's concepts from textual data. The preliminary results highlight the efficiency of our proposal for ontology population. [ABSTRACT FROM AUTHOR]

First-order compartment models are common tools for modelling many biological processes, including pharmacokinetics. Given the compartments and the transfer rates, solutions for the time-dependent quantity (or concentration) curves can normally be described by a sum of exponentials. This paper investigates cases that go beyond simple sums of exponentials. With specific relations between the transfer rate constants, two exponential rate constants can be equal, in which case the normal solution cannot be used. The conditions for this to occur are discussed, and advice is provided on how to circumvent these cases. An example of an analytic solution is given for the rare case where an exact equality is the expected result. Furthermore, for models with at least three compartments, cases exist where the solution to a real-valued model involves complex-valued exponential rate constants. This leads to solutions with an oscillatory element in the solution for the tracer concentration, i.e., there are cases where the solution is not a simple sum of (real-valued) exponentials but also includes sine and cosine functions. Detailed solutions for three-compartment cases are given. As a tentative conclusion of the analysis, oscillatory solutions appear to be tied to cases with a cyclic element in the model itself. [ABSTRACT FROM AUTHOR]

Rutin is a flavonoid present in numerous fruits and vegetables and therefore widely consumed by humans. It is also a popular dietary supplement of 250–500 mg/day. There is considerable consumer interest in rutin due to numerous reports in the biomedical literature of its multi-system chemo-preventive properties. The present paper provides the first assessment of rutin-induced hormetic concentration/dose responses, their quantitative features and mechanistic basis, along with their biological, biomedical, clinical, and public health implications. The findings indicate that rutin-induced hormetic dose responses are widespread, being reported in numerous biological models and cell types for a wide range of endpoints. Of critical importance is that the optimal hormetic findings shown in in vitro systems are currently not achievable for human populations due to low gastrointestinal tract bioavailability. These findings have the potential to strengthen future experimental studies with rutin, particularly concerning study design parameters. [Display omitted] • Rutin is a flavonoid present in fruits and vegetables consumed by humans. • Rutin displays multi-system chemo-preventive properties. • First assessment of rutin-induced hormetic dose responses and its implications. • Several biological models and cells show rutin-induced hormetic dose responses. • Findings have the potential to strengthen future experimental studies with rutin. [ABSTRACT FROM AUTHOR]

The learning of QSAR/QSPR models is crucial for predicting the physicochemical properties/biological activities of compounds. For compounds with the same/similar structure, there is a high probability that the molecular descriptors describing the molecular structure undergo degeneracy such that it is impossible to distinguish between these compounds, which in turn leads to modeling failure. In this paper, we construct a two-layer graph structure to design new feature descriptors with high discriminability, and propose a graph signal processing (GSP)-based method for nonlinear QSAR/QSPR model learning for compounds. Considering the molecular descriptors computed based on the molecular graph as a high-dimensional signal, we construct on top of the molecular graph a higher-level graph structure – a compound graph – to describe the similarity between different compounds. We use local complex network metrics to quantify the local topological information on each vertex (compound) in the compound graph, which can naturally be used as new discriminative feature descriptors, based on which we learn two types of nonlinear QSAR/QSPR models. Three datasets with the same/similar molecular graphs are used to learn to model their biological activity, entropy and octanol–water partition coefficient, respectively, and the experimental results well validate the effectiveness of the proposed method. • A GSP-based method for nonlinear QSAR/QSPR model learning of compounds. • Two-layer graph structure to design new feature descriptors with high discriminability. • Three different polynomial/SVR models for three datasets with compounds having the same/similar structure. [ABSTRACT FROM AUTHOR]

The sequences play an important role on many application areas. The strings as symbol sequences are investigated mainly in natural language processing and biological modeling. This paper investigates the transformation process of the strings and it proposes a method for induction of the string transformation rules. The presented method is based on the application of an FCA lattice for generalization of the transformation rules. The paper introduces an efficient construction algorithm for building the conceptualization lattice. Based on the performed comparison tests, the proposed method outperforms the main incremental methods and for some parameter ranges, its efficiency is comparable with the efficiency of the best batch methods. [ABSTRACT FROM AUTHOR]

This paper represents the first integrative assessment and documentation of taurine-induced hormetic effects in the biological and biomedical areas, their dose response features, mechanistic frameworks, and possible public health, therapeutic and commercial applications. Taurine-induced hormetic effects are documented in a wide range of experimental models, cell types and for numerous biological endpoints, with most of these experimental findings being reported within the past five years. It is suggested that the concept of hormesis may have a transformative effect on taurine research and its public health and therapeutic applications. • Hormesis is a biphasic dose response relationship. • Taurine commonly induces hormetic dose responses. • Numerous tissues show taurine-induced hormesis. • Taurine acts via activation of Nrf2 to induce hormetic effects. [ABSTRACT FROM AUTHOR]

Quercetin is a polyphenol present in numerous fruits and vegetables and therefore widely consumed by humans with average daily dietary intakes of 10–20 mg/day. It is also a popular dietary supplement of 250-1000 mg/day. However, despite the widespread consumer interest in quercetin, due to its possible chemopreventive properties, the extensively studied quercetin presents a highly diverse and complex array of biological effects. Consequently, the present paper provides the first assessment of quercetin-induced hormetic concentration/dose responses, their quantitative features and mechanistic foundations, and their biological, biomedical, clinical, and public health implications. The findings indicate that quercetin-induced hormetic dose responses are widespread, being independent of biological model, cell type, and endpoint. These findings have the potential to enlighten future experimental studies with quercetin especially with respect to study design parameters and may also affect the appraisal of possible public health benefits and risks associated with highly diverse consumer consumption practices. • Quercetin commonly induces hormetic responses. • Hormetic responses induced by quercetin occur in numerous cell types. • Hormetic mechanisms have been reported in numerous studies. • Public health applications are provided. [ABSTRACT FROM AUTHOR]

Craniofacial reconstruction recreates a facial outlook from the cranium based on the relationship between the face and the skull to assist identification. But craniofacial structures are very complex, and this relationship is not the same in different craniofacial regions. Several regional methods have recently been proposed, these methods segmented the face and skull into regions, and the relationship of each region is then learned independently, after that, facial regions for a given skull are estimated and finally glued together to generate a face. Most of these regional methods use vertex coordinates to represent the regions, and they define a uniform coordinate system for all of the regions. Consequently, the inconsistence in the positions of regions between different individuals is not eliminated before learning the relationships between the face and skull regions, and this reduces the accuracy of the craniofacial reconstruction. In order to solve this problem, an improved regional method is proposed in this paper involving two types of coordinate adjustments. One is the global coordinate adjustment performed on the skulls and faces with the purpose to eliminate the inconsistence of position and pose of the heads; the other is the local coordinate adjustment performed on the skull and face regions with the purpose to eliminate the inconsistence of position of these regions. After these two coordinate adjustments, partial least squares regression (PLSR) is used to estimate the relationship between the face region and the skull region. In order to obtain a more accurate reconstruction, a new fusion strategy is also proposed in the paper to maintain the reconstructed feature regions when gluing the facial regions together. This is based on the observation that the feature regions usually have less reconstruction errors compared to rest of the face. The results demonstrate that the coordinate adjustments and the new fusion strategy can significantly improve the craniofacial reconstructions. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with a parabolic–elliptic model for biological fluid transportation networks with the large diffusivity and activation. Our investigations reveal that local existence of the unique classical solution to the correspondinginitial–boundary value problem can always be achieved in the n -dimensional setting with n ≤ 3. Moreover, we show that this local solution can be extended to a global one as long as the source term and the initial data are made small enough in a suitable sense, and that the classical solution converges exponentially to a trivial steady state; meanwhile, we present that the smallness condition on the initial data can be removed in the one-dimensional setting. Our result implies that we cannot expect network formation when the diffusivity is sufficiently large, which is a first step toward a qualitative analysis for the role of diffusion in biological transportation networks. [ABSTRACT FROM AUTHOR]

Network topology has a critical effect on its reliability. Due to the complexity of networks, how to design a more reliable network topology is one of the fascinating and significant challenges. In this paper, inspired by the multi-scale model of biological systems which range from gene to individual cells, and up to the individual organism, we provide a novel method to design a reliable topology of large-scale networks. By means of fractal theory and its application in complex networks, a network topology can be described as consisting of the superposition of basic units, called fractal-cells, which are made up of several components and their connections. Based on this fractal-cell structure, we find that a fractal-cell network has structural similarity with its primitive structure, and then develop a method to build a reliable topology which is generated from a primitive ring structure. Numerical simulation compared with the existing methods and performing on real networks show that our proposed method is effective. • The network topology can be described as consisting of the superposition of basic units, called fractal-cells. • Through the fractal-cell division and differentiation, we find that a fractal-cell network has structural similarity with its primitive structure. • A novel method is proposed to build a reliable topology based on fractal-cell division and differentiation. [ABSTRACT FROM AUTHOR]

• An unsymmetric 8-node hexahedral element without additional DOF is developed for modeling biological tissues. • The analytical general solutions for anisotropic elasticity are firstly employed in trial functions. • The element performance is validated by commonly used benchmarks and cardiac examples. • The present formulation possesses high accuracy, fast convergence rates and is quite insensitive to mesh distortion. • The present formulation is free of various locking in modeling nearly-incompressible problems. In biomechanics problems, the biological soft tissues are usually treated as anisotropic nearly incompressible hyperelastic materials, but such complicated nonlinear material models often cause challenging problems of severe volumetric locking and instabilities in numerical simulations. In this paper, the recent unsymmetric 8-node, 24-DOF hexahedral solid element US-ATFH8 with different test and analytical trial functions (ATFs) is modified for the analysis of the anisotropic nearly-incompressible hyperelastic soft tissues. Unlike the original formulation, the linear analytical general solutions for anisotropic elasticity and the consistent tangent modulus are firstly employed for formulating the trial functions, and are used to construct the incremental displacement fields that result in the incremental deformation gradient. The total deformation gradient is obtained by multiplying the incremental deformation gradient by the deformation gradient, after which the Cauchy stresses can be directly calculated from a total-form constitutive equation relating to the deformation gradient. Numerical tests, including commonly used benchmarks and cardiac examples, demonstrate attractive properties of the proposed finite element formulation in modeling nearly-incompressible anisotropic hyperelastic materials. It is free of various locking and quite insensitive to mesh distortions, and provides high accuracy with faster convergence rates when compared with other existing models. [Display omitted] [ABSTRACT FROM AUTHOR]

Blunt force trauma is the most common injury found during autopsies. Among the cases involving blunt force injuries, fractures to the skull are the most frequent, and these are often fatal to the victim. Understanding the circumstances surrounding the creation of such injuries is essential for investigating trauma-related deaths. This paper explores the characteristics of cranial trauma produced following one to three consecutive blows with a series of blunt objects. Fourteen Synbone® spheres filled with porcine gelatine and coated with rubber skin were used to simulate the human skull in a series of experiments. Trials recreated two scenarios, individuals standing and individuals with their head resting against a hard surface. Six blunt objects were used to represent possible weapons. Each sphere was struck twice to generate fracture patterns, which were then analysed. In most simulations of a blow to the head resting against a hard surface, the first fracture follows a linear pattern regardless of the direction of force and/or the surface of the weapon; while the second blow results in a depressed fracture. In the case of a free moving head, weapons with large contact surfaces result in depressed fractures, while weapons with small contact surfaces may not cause a fracture at all. Our results are consistent with Moritz who stated that, if the head is free to move, the fractures will be linear or incompletely depressed. Inversely, if the head rests against a solid surface, a blow will result in a depressed fracture. More experiments are needed to verify these preliminary observations. [ABSTRACT FROM AUTHOR]

Boolean networks are a well-established formalism for modelling biological systems. An important aspect of analysing a Boolean network is to identify all its attractors. This becomes challenging for large Boolean networks due to the infamous state-space explosion problem. In this paper, we propose a new strongly connected component (SCC) based decomposition method for attractor detection in large synchronous Boolean networks and prove its correctness. Experimental results show that our proposed method is significantly better in terms of performance when compared to existing methods in the literature. [ABSTRACT FROM AUTHOR]

The present paper aims to assess the risk of rib fractures caused by any rigid less-lethal kinetic energy projectiles. To that end, a coupled experimental and numerical approach is proposed to relate ballistic experiments with the risk of blunt trauma. A polymer gel block is employed as ballistic testing medium to interpret ballistic impacts through the measurement of the dynamic gel wall displacement. Moreover, a biofidelic 50th percentile human torso finite element model created in the code Hypermesh (Altair HyperWorks ©) is used to replicate experiments and real world accidents. Then, the probability curve of rib fractures is a function of the viscous criterion and derives from a study on human cadaver mid-sternum available in the literature. Twelve impact conditions of rigid projectiles are applied to a SEBS gel block and are replicated on the human torso model mid-sternum. A statistical analysis is performed by virtue of a Spearman's correlation matrix in order to identify relations between experimental measurements and the viscous criterion evaluated numerically. The determination of both statistical significances and correlation coefficients results in several strong correlations between experimental measurements and the viscous criterion evaluated numerically. These relations imply the establishment of transfer functions between experimental metrics on the gel block (the maximum gel wall displacement and a gel wall displacement - rate of displacement based metric) and the probability of rib fractures. Finally, these correlations constitute a primary and an up-and-coming predicting tool for the risk of rib fractures. [ABSTRACT FROM AUTHOR]

Convolutional Neural Networks have been proposed as suitable frameworks to model biological vision. Some of these artificial networks showed representational properties that rival primate performances in object recognition. In this paper we explore how color is encoded in a trained artificial network. It is performed by estimating a color selectivity index for each neuron, which allows us to describe the neuron activity to a color input stimuli. The index allows us to classify whether they are color selective or not and if they are of a single or double color. We have determined that all five convolutional layers of the network have a large number of color selective neurons. Color opponency clearly emerges in the first layer, presenting 4 main axes (Black-White, Red-Cyan, Blue-Yellow and Magenta-Green), but this is reduced and rotated as we go deeper into the network. In layer 2 we find a denser hue sampling of color neurons and opponency is reduced almost to one new main axis, the Bluish-Orangish coinciding with the dataset bias. In layers 3, 4 and 5 color neurons are similar amongst themselves, presenting different type of neurons that detect specific colored objects (e.g., orangish faces), specific surrounds (e.g., blue sky) or specific colored or contrasted object-surround configurations (e.g. blue blob in a green surround). Overall, our work concludes that color and shape representation are successively entangled through all the layers of the studied network, revealing certain parallelisms with the reported evidences in primate brains that can provide useful insight into intermediate hierarchical spatio-chromatic representations. [ABSTRACT FROM AUTHOR]

When humans (or robots) move through a scene, the scene can be represented as an optic flow (optical flow) field that contains vectors representing all of the movement within the scene projected onto a two-dimensional sensor. A simultaneous sample of these resulting vectors contain a good deal of information. A general model of motion estimation of local vectors would therefore be valuable. This paper addresses the estimation of motion vectors with uniform motion over a fixed time period. Previous reported attempts at computing motion estimation have been dominated by the machine vision community; however, these attempts are not specifically concerned with biological plausibility. Here, the author presents a model of motion estimation that computes motion based on filtering the moving image into sinusoidal responses varying in spatial frequency and orientation similar to the early visual responses found in human vision. Unlike similar spatio-temporal energy models "motion energy" is not computed. The model is mathematically explicit and simulated in MATLAB. It has been tested using over 7000 synthetic moving images with known veridical velocity (ground truth). These images range from sparse translating patterns containing 1 to 10,000 random pixels, to dense narrow band sinusoidal patterns. Simulation results show that the model correctly estimates motion trajectories between 84% and 100% angular direction error (within ±2°), and displacement error (within ±1 pixel). The results remain robust at different contrasts. In addition, a number of psychophysical and physiological results are examined in the context of the model. [ABSTRACT FROM AUTHOR]

In homicide investigations, it is critically important that post-mortem (PMI) and post-burial interval (PBI) of buried victims are determined accurately. However, clandestine graves can be difficult to locate; and the detection rates for a variety of search methods can be very low. This paper presents elemental analysis results of 18 months of decomposition fluids from an in situ buried animal cadaver used as a human clandestine burial proxy. Study results showed potassium, sulphate and sodium are key detectable elements which mirror observed conductivity temporal changes from this and other studies. Seasonal rainfall has a strong influence on both fluid generation and subsequent concentration which needs to be accounted for. Study implications suggest inorganic elements could provide both detection and potential dating of discovered clandestine burials. [ABSTRACT FROM AUTHOR]

The brain connections in the different regions demonstrate the characteristics of brain activities. In addition, in various conditions and with neuropsychological disorders, the brain has special patterns in different regions. This paper presents a model to show and compare the connection patterns in different brain regions of children with autism (53 boys and 36 girls) and control children (61 boys and 33 girls). The model is designed by cellular neural networks and it uses the proper features of electroencephalography. The results show that there are significant differences and abnormalities in the left hemisphere, (p < 0.05) at the electrodes AF3, F3, P7, T7, and O1 in the children with autism compared with the control group. Also, the evaluation of the obtained connections values between brain regions demonstrated that there are more abnormalities in the connectivity of frontal and parietal lobes and the relations of the neighboring regions in children with autism. It is observed that the proposed model is able to distinguish the autistic children from the control subjects with an accuracy rate of 95.1% based on the obtained values of CNN using the SVM method. [ABSTRACT FROM AUTHOR]

Thermoregulation models of the human body have been widely used in thermal comfort studies. The existing models are complicated and not fully verified for application in China. This paper presents a simplified thermoregulation model which has been statistically validated by the predicted and measured mean skin temperature in warm environments, including 21 typical conditions with 400 Chinese subjects. This model comprises three parts: i) the physical model; ii) the controlled system; and iii) the controlling system, and considers three key questions formerly ignored by the existing models including: a) the evaporation efficiency of regulatory sweat; b) the proportional relation of total skin blood flow and total heat loss by regulatory sweating against body surface area; and c) discrepancies in the mean skin temperatures by gender. The developed model has been validated to be within the 95% confidence interval of the population mean skin temperature in three cases. [ABSTRACT FROM AUTHOR]

In this paper, we study an existence theory as well as stability results to the new fractional Nabla difference biological model of glucose–insulin regulatory system (GIRS) on diabetes mellitus involving the Atangana Baleanu–Caputo (ABC) derivative. We consider the proposed model under ABC derivative, and it has the nonsingular Mittag-Leffler function as its kernel. We utilize the fixed point technique for the existence and uniqueness analysis. The stability of the concerned solution in Hyers–Ulam sense is also investigated. Further to derive the approximate solution in the form of series to the considered model, we use iterative technique method. Numerical simulations are given to support the theoretical results. The results show that order of the fractional derivative has a significant effect on the dynamic process. Many informations on the dynamics of GIRS in diabetes mellitus were obtained using this model. It is recognized as a deterministic fractional Nabla difference model for diabetes mellitus that provides a better control approach at fractional values for the development of an artificial pancreas. [ABSTRACT FROM AUTHOR]

Microbially mediated mechanisms of human decomposition begin immediately after death, and are a driving force for the conversion of a once living organism to a resource of energy and nutrients. Little is known about post-mortem microbiology in cadavers, particularly the community structure of microflora residing within the cadaver and the dynamics of these communities during decomposition. Recent work suggests these bacterial communities undergo taxa turnover and shifts in community composition throughout the post-mortem interval. In this paper we describe how the microbiome of a living host changes and transmigrates within the body after death thus linking the microbiome of a living individual to post-mortem microbiome changes. These differences in the human post-mortem from the ante-mortem microbiome have demonstrated promise as evidence in death investigations. We investigated the post-mortem structure and function dynamics of Staphylococcus aureus and Clostridium perfringens after intranasal inoculation in the animal model Mus musculus L. (mouse) to identify how transmigration of bacterial species can potentially aid in post-mortem interval estimations. S. aureus was tracked using in vivo and in vitro imaging to determine colonization routes associated with different physiological events of host decomposition, while C. perfringens was tracked using culture-based techniques. Samples were collected at discrete time intervals associated with various physiological events and host decomposition beginning at 1h and ending at 60 days post-mortem. Results suggest that S. aureus reaches its highest concentration at 5-7 days post-mortem then begins to rapidly decrease and is undetectable by culture on day 30. The ability to track these organisms as they move in to once considered sterile space may be useful for sampling during autopsy to aid in determining post-mortem interval range estimations, cause of death, and origins associated with the geographic location of human remains during death investigations. [ABSTRACT FROM AUTHOR]

Scores of visual attention models have been developed over the past several decades of research. Differences in implementation, assumptions, and evaluations have made comparison of these models very difficult. Taxonomies have been constructed in an attempt at the organization and classification of models, but are not sufficient at quantifying which classes of models are most capable of explaining available data. At the same time, a multitude of physiological and behavioral findings have been published, measuring various aspects of human and non-human primate visual attention. All of these elements highlight the need to integrate the computational models with the data by (1) operationalizing the definitions of visual attention tasks and (2) designing benchmark datasets to measure success on specific tasks, under these definitions. In this paper, we provide some examples of operationalizing and benchmarking different visual attention tasks, along with the relevant design considerations. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new framework to predict visual scanpaths of observers while they freely watch a visual scene. The visual fixations are inferred from bottom-up saliency and several oculomotor biases. Bottom-up saliency is represented by a saliency map whereas the oculomotor biases (saccade amplitudes and saccade orientations) are modeled using public eye tracking datasets. Our experiments show that the simulated scanpaths exhibit similar trends of human eye movements in a free-viewing condition. The generated scanpaths are more similar to human scanpaths than those generated by two existing methods. In addition, we show that computing saliency maps from simulated visual scanpaths allows to outperform existing saliency models. [ABSTRACT FROM AUTHOR]

The brine shrimp, Artemia spp., is widely used in ecotoxicology as a target biological model. Although several protocols were available in the early 1980s, only the 24-h acute mortality toxicity test was evaluated in a European intercalibration exercise during that period. Nevertheless, documentation of standard methods serving to provide specifications, guidelines or detailed characteristics of the 24-h protocol is still unavailable. This paper present the results of an intercalibration study of three toxicity-testing protocols using Artemia franciscana : (a) the 24-h static acute mortality test, (b) the 48-h static hatching test and (c) the 14-d static-renewal long-term mortality test. A first tier of experiments was conducted by a reference laboratory, which investigated the repeatability of the three methods. The feasibility and reproducibility of these protocols were then investigated by an intercomparison exercise involving 11 participants for the acute mortality test, seven for the acute hatching test and nine for the long-term mortality test. Protocols were tested on reference toxicants (copper sulphate pentahydrate and sodium dodecyl sulphate). The coefficients of variation were <20% and <50% for intra- and interlaboratory activities, respectively. These results encourage the standardization of the proposed methods and their use as regulatory procedures. [ABSTRACT FROM AUTHOR]

In this paper we describe various limited-stretch models of non-linear rubber elasticity, each dependent on only the first invariant of the left Cauchy–Green strain tensor and having only two independent material constants. The models are described as limited-stretch, or restricted elastic, because the strain energy and stress response become infinite at a finite value of the first invariant. These models describe well the limited stretch of the polymer chains of which rubber is composed. We discuss Gent׳s model which is the simplest limited-stretch model and agrees well with experiment. Various statistical models are then described: the one-chain, three-chain, four-chain and Arruda–Boyce eight-chain models, all of which involve the inverse Langevin function. A numerical comparison between the three-chain and eight-chain models is provided. Next, we compare various models which involve approximations to the inverse Langevin function with the exact inverse Langevin function of the eight-chain model. A new approximate model is proposed that is as simple as Cohen׳s original model but significantly more accurate. We show that effectively the eight-chain model may be regarded as a linear combination of the neo-Hookean and Gent models. Treloar׳s model is shown to have about half the percentage error of our new model but it is much more complicated. For completeness a modified Treloar model is introduced but this is only slightly more accurate than Treloar׳s original model. For the deformations of uniaxial tension, biaxial tension, pure shear and simple shear we compare the accuracy of these models, and that of Puso, with the eight-chain model by means of graphs and a table. Our approximations compare extremely well with models frequently used and described in the literature, having the smallest mean percentage error over most of the range of the argument. [ABSTRACT FROM AUTHOR]

• Synthesis of Schiff's base from furfural and sulfanilamide. • Detailed structure, FTIR, PED, Vibrational assignment, 1HNMR, 13CNMR and UV reported. • Interaction between solvent water and compound analyzed using RDG and EDA. • Antimicrobial study and docking indicate moderate activity. • Wave function studies also reported in this paper. A new Schiff base (Z)-4-((furan-2-ylmethylene)amino)benzenesulfonamide (FURNI) was synthesized by the reaction reaction between furfural and sulfanilamide followed by characterization using IR, UV–Visible, 1HNMR, and 13CNMR spectral techniques. This was followed by electronic structure studies using DFT and TD-DFT. We simulated the IR spectrum using B3LYP/aug-ccPVDZ level of theory, followed by a comparison with experimental spectra and detailed potential energy distribution and vibrational assignment analysis. The comparison of experimental UV and simulated UV spectrum using TD-DFT CAM-B3LYP/ aug-ccPVDZ in DMSO solvent atmosphere gave good agreement. The compound is found to interact with the solvent water molecule. Energy decomposition analysis showed that there exists a strong hydrogen bond between the compound and the solvent water. As Schiff bases are biologically active, we checked for the potential activity of the synthesized compound with the help of ADMET prediction and found it to be active. Wavefunctions related properties like ELF, ALIE, LOL, and ELF are also reported. Prediction of biological activity spectrum study indicated possible antimicrobial activity against bacteria and fungus, which is supported by molecular docking against human mitochondrial (2WYA) protein with a docking score of −7.2 kcal/mol. Experimental antibacterial and antifungal studies using the compound and standard drugs confirmed this prediction. [ABSTRACT FROM AUTHOR]

The paper investigates peculiarities of infection evolution and spreading models in non-uniform biological systems of individuals (humans, animals, plants) using the approach of mathematical modeling. The effects of different characteristic features are revealed. A robust tool for prediction of infection evolution (growth and spreading) under different external conditions is developed accounting for spatial non-uniformity of governing parameters. • Peculiarities of infection evolution and spreading models in non-uniform systems studied. • Evolution of systems of individuals (humans, animals, plants) is subject for mathematical modeling. • The effects of different characteristic features are revealed. • A robust tool for prediction of infection evolution is developed accounting for spatial non-uniformity. [ABSTRACT FROM AUTHOR]

We study a simplified version of a class of constitutive relations used to describe large deformations of soft tissues, where the elastic energy density involves an exponential term. The class was originally introduced by Y.C. Fung as a model of many biological soft tissues in a series of papers during the Seventies. We prove existence and uniqueness of the equilibrium solution for a general measure-valued external load, under quite general boundary conditions, and study the validity of the associated Euler–Lagrange equation in the sense of distributions. • A class of hyperelastic materials involving an exponential term is studied. • We prove existence and uniqueness of the equilibrium solution for a general measure-valued external load. • The validity of the associated Euler–Lagrange equation in the sense of distributions is proved. [ABSTRACT FROM AUTHOR]

Physics-constrained data-driven computing is an emerging computational paradigm that allows simulation of complex materials directly based on material database and bypass the classical constitutive model construction. However, it remains difficult to deal with high-dimensional applications and extrapolative generalization. This paper introduces deep learning techniques under the data-driven framework to address these fundamental issues in nonlinear materials modeling. To this end, an autoencoder neural network architecture is introduced to learn the underlying low-dimensional representation (embedding) of the given material database. The offline trained autoencoder and the discovered embedding space are then incorporated in the online data-driven computation such that the search of optimal material state from database can be performed on a low-dimensional space, aiming to enhance the robustness and predictability with projected material data. To ensure numerical stability and representative constitutive manifold, a convexity-preserving interpolation scheme tailored to the proposed autoencoder-based data-driven solver is proposed for constructing the material state. In this study, the applicability of the proposed approach is demonstrated by modeling nonlinear biological tissues. A parametric study on data noise, data size and sparsity, training initialization, and model architectures, is also conducted to examine the robustness and convergence property of the proposed approach. • Autoencoder based data-driven modeling approach is proposed for nonlinear materials. • Autoencoders enable noise filtering and dimensionality reduction of material data. • Convexity-preserving interpolation is employed for enhanced stability in data search. • Improved generalization capability is demonstrated by modeling biological tissues. [ABSTRACT FROM AUTHOR]

• Biologically inspired heuristics for target search lack modularity and modifiability. • The proposed hyper-heuristic is based on modular and adaptive swarm behavior. • Combining stigmergy, flocking and evolution outperforms bio-inspired heuristics. Target search aims to discover elements of various complexity in a physical environment, by minimizing the overall discovery time. Different swarm intelligence algorithms have been proposed in the literature, inspired by biological species. Despite the success of bio-inspired techniques (bio-heuristics), there are relevant algorithm selection and parameterization costs associated with every new type of mission and with new instances of known missions. In this paper, evolutionary optimization is proposed for achieving significant improvements of the mission performance. Although adaptive, the logic of bio-heuristics is nevertheless constrained by models of biological species. To generate more adaptable logics, a novel design approach based on hyper-heuristics is proposed, in which the differential evolution optimizes the aggregation and tuning of modular heuristics for a given application domain. A modeling and optimization testbed has been developed and publicly released. Experimental results on real-world scenarios show that the hyper-heuristics based on stigmergy and flocking significantly outperform the adaptive bio-heuristics. [Display omitted] [ABSTRACT FROM AUTHOR]

Biomimetics is an opportunity for the development of energy efficient building systems. Several biomimetic building skins (Bio-BS) have been built over the past decade, however few addressed multi-regulation although the biological systems they are inspired by have multi-functional properties. Recent studies have suggested that despite numerous tools and methods described in the literature for the development of biomimetic systems, their use for designing Bio-BS is scarce. To assess the main challenges of biomimetic design processes and their influence on the final design, this paper presents a comparative analysis of several existing Bio-BS. The analyses were carried out with univariable and multivariate descriptive tools in order to highlight the main trends, similarities and differences between the projects. The authors evaluated the design process of thirty existing Bio-BS, including a focus on the steps related to the understanding of the biological models. Data was collected throughout interviews. The univariate analysis revealed that very little Bio-BS followed a biomimetic design framework (5%). None of the Bio-BS was as multi-functional as their biological model(s) of inspiration. A further conclusion drawn that Bio-BS are mostly inspired by single biological organisms (82%), which mostly belong to the kingdom of animals (53%) and plants (37%). The multivariate analysis outlined that the Bio-BS were distributed into two main groups: (1) academic projects which present a strong correlation with the inputs in biology in their design processes and resulted in radical innovation; (2) public building projects which used conventional design and construction methods for incremental innovation by improving existing building systems. These projects did not involve biologists neither a thorough understanding of biological models during their design process. Since some biomimetic tools are available and Bio-BS have shown limitations in terms of multifunctionality, there is a need to promote the use of multidisciplinary tools in the design process of Bio-BS, and address the needs of the designers to enhance the application of multi-regulation capabilities for improved performances. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a reaction–diffusion–advection two-species competition biological model by employing the methods of Lyapunov–Schmidt reduction, perturbation theory and the implicit function theorem and so on. For any given diffusion rates we obtain the existence of positive steady states by using the advection rate η and the competitive coefficients c and b as the bifurcation parameters. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via the original article. [ABSTRACT FROM AUTHOR]

In this paper, the two biological models i.e. Nitrogen, Phytoplankton and Zooplankton (NPZ) and whooping cough SIR models (Charpentier et al., 2010) are being modified and solved numerically by finite difference and meshless methods. Diffusion process has been added to the existing models (Charpentier et al., 2010) so that a unidimensional movement of three species can be incorporated in the models. The effects of diffusion has been studied in both the models. An operator splitting method coupled with the meshless and finite difference procedures, is being considered for numerical solution of the two biological models with and without diffusion. A one step explicit meshless procedure is also applied for the numerical solution of the nonlinear models. The NPZ model contains the concentration of Nitrogen, Phytoplankton and Zooplankton and the whooping cough model contains susceptible, infected, and recovered classes of the population. Equilibrium points of both models have been investigated. Stability of equilibrium points regarding SIR model has been studied. The basic reproduction number of SIR model is also determined. Due to non-availability of the exact solution, the numerical results obtained are mutually compared and their correctness is being verified by the theoretical results as well. • In this manuscript we modify Nitrogen, Phytoplankton and Zooplankton (NPZ) and whooping cough (SIR) models by adding diffusion process. • A new operating splitting method based on Meshless method and Finite difference method is used for the numerical simulation. • A one step explicit meshless procedure is also applied for the numerical solution of the nonlinear models. [ABSTRACT FROM AUTHOR]

Methods: The aim of the paper is twofold. First, we present Starviewer, a DICOM viewer developed in C++ with a core component built on top of open-source libraries. The viewer supports extensions that implement functionalities and front-ends for specific use cases. Second, we propose an adaptable evaluation framework based on a set of criteria weighted according to user needs. The framework can consider different user profiles and allow criteria to be decomposed in subcriteria and grouped in more general categories making a multi-level hierarchical structure that can be analysed at different levels of detail to make scores interpretation more comprehensible.Results: Different examples to illustrate Starviewer functionalities and its extensions are presented. In addition, the proposed evaluation framework is used to compare Starviewer with four open-source viewers regarding their functionalities for daily clinical practice. In a range from 0 to 10, the final scores are: Horos (7.7), Starviewer (6.2), Weasis (6.0), Ginkgo CADx (4.1), and medInria (3.8).Conclusions: Starviewer provides basic and advanced features for daily image diagnosis needs as well as a modular design that enables the development of custom extensions. The evaluation framework is useful to understand and prioritize new development goals, and can be easily adapted to express different needs by altering the weights. Moreover, it can be used as a complement to maturity models. [ABSTRACT FROM AUTHOR]

In stochastic financial and biological models, the diffusion coefficients often involve the term x , or more general | x | r for r ∈ (0 , 1) , which is non-Lipschitz. In this paper, we study the strong convergence of the truncated Euler–Maruyama (EM) approximation first proposed by Mao (2015) for one-dimensional stochastic differential equations (SDEs) with superlinearly growing drifts and the Hölder continuous diffusion coefficients. [ABSTRACT FROM AUTHOR]

Familial search is a statistical approach that is used to infer genetic relationships between a forensic sample and individuals in a DNA database. Several authors have proposed likelihood ratio-based statistics for testing parent-child and full sibling relationships when population substructure exists. This paper proposes three new statistics and investigates performance of each statistic based on Type I error and power. Three statistics, defined by (1) the local allele frequency, (2) the Balding-Nichols approach and (3) the ratio between the maximum of the genotype probabilities over racial subgroup, were found to be good for testing these two types of familial relationships. Power analyses within racial groups are also included, with the power highest for African-American samples and lowest for Caucasian samples. Finally, simulation studies were done on both original and extended CODIS core loci. There were clear differences in power, with the power substantially higher for extended CODIS core loci. [ABSTRACT FROM AUTHOR]