An integrated systems biology approach to understanding the rules of keratinocyte colony formation.

Closely coupled in vitro and in virtuo models have been used to explore the self-organization of normal human keratinocytes (NHK). Although it can be observed experimentally, we lack the tools to explore many biological rules that govern NHK self-organization. An agent-based computational model was developed, based on rules derived from literature, which predicts the dynamic multicellular morphogenesis of NHK and of a keratinocyte cell line (HaCat cells) under varying extracellular Ca++ concentrations. The model enables in virtuo exploration of the relative importance of biological rules and was used to test hypotheses in virtuo which were subsequently examined in vitro. Results indicated that cell-cell and cell-substrate adhesions were critically important to NHK self-organization. In contrast, cell cycle length and the number of divisions that transit-amplifying cells could undergo proved non-critical to the final organization. Two further hypotheses, to explain the growth behaviour of HaCat cells, were explored in virtuo-an inability to differentiate and a differing sensitivity to extracellular calcium. In vitro experimentation provided some support for both hypotheses. For NHKs, the prediction was made that the position of stem cells would influence the pattern of cell migration post-wounding. This was then confirmed experimentally using a scratch wound model.     

Computational design strategy: an approach to enhancing the transdermal delivery of optimal capsaicin-loaded transinvasomes

Abstract

The aim of this study was to design and develop simultaneous optimal transinvasome formulations (OTV) to enhance the transdermal delivery of capsaicin. Using a central composite experimental design with duplicate centroids, 10 model formulations of transinvasomes (TVs) were demonstrated. The lipid compositions of the TV formulations were determined as formulation factors (X_n) and response variables (Y_n), respectively. TV formulations containing a constant concentration of phosphatidylcholine, cholesterol, 0.15% capsaicin, and various percentages of d-limonene (X₁) and cocamide diethanolamine (X₂) were prepared. The physicochemical characteristics, e.g. the vesicle size, size distribution, zeta potential, entrapment efficiency, and skin permeability, of the TV formulations were experimentally investigated. The relationship among the formulation factor, the response variables, and the OTV was predicted using Design Expert^® software. The accuracy and reliability of the OTV predicted using computer software were experimentally confirmed and investigated as an experimental transinvasome formulation (ETV). The results indicated that the skin permeability of the ETV was close to the OTV and was significantly higher than that of conventional liposomes and commercial products. The response surfaces estimated by the computer software were helpful in understanding the complicated relationship among the formulation factor, the response variables, and the stability of the TV formulation.     

Go with the FLOW: visualizing spatiotemporal dynamics in optical widefield calcium imaging

Widefield calcium imaging has recently emerged as a powerful experimental technique to record coordinated large-scale brain activity. These measurements present a unique opportunity to characterize spatiotemporally coherent structures that underlie neural activity across many regions of the brain. In this work, we leverage analytic techniques from fluid dynamics to develop a visualization framework that highlights features of flow across the cortex, mapping wavefronts that may be correlated with behavioural events. First, we transform the time series of widefield calcium images into time-varying vector fields using optic flow. Next, we extract concise diagrams summarizing the dynamics, which we refer to as FLOW (flow lines in optical widefield imaging) portraits. These FLOW portraits provide an intuitive map of dynamic calcium activity, including regions of initiation and termination, as well as the direction and extent of activity spread. To extract these structures, we use the finite-time Lyapunov exponent technique developed to analyse time-varying manifolds in unsteady fluids. Importantly, our approach captures coherent structures that are poorly represented by traditional modal decomposition techniques. We demonstrate the application of FLOW portraits on three simple synthetic datasets and two widefield calcium imaging datasets, including cortical waves in the developing mouse and spontaneous cortical activity in an adult mouse.     

An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information

Nowadays selecting the most suitable robot is a difficult task for manufacturing firms due to increase in production demands and availability of various robot models. Robot evaluation and selection can be regarded as a multiple criteria decision-making (MCDM) problem and three key issues are the assessment of robots, the determination of criteria weights and the prioritisation of alternatives. This paper aims to propose an integrated model based on hesitant 2-tuple linguistic term sets and an extended QUALIFLEX approach for handling robot selection problems with incomplete weight information. The new model can not only manage uncertain and imprecise assessment information of decision-makers with the aid of hesitant 2-tuple linguistic term sets, but also derive the important weights of criteria objectively when the weight information is incompletely known. Moreover, based on the extended QUALIFLEX algorithm, the priority orders of robots can be clearly determined and a more reasonable and credible solution can be yielded in a particular industrial application. Finally, a robot selection case study is carried out, and comparative experiments indicate the practicality and effectiveness of the proposed integrated linguistic MCDM approach.     

Multi-Scale 3D U-Nets: An approach to automatic segmentation of brain tumor

Gliomas segmentation is a critical and challenging task in surgery and treatment, and it is also the basis for subsequent evaluation of gliomas. Magnetic resonance imaging is extensively employed in diagnosing brain and nervous system abnormalities. However, brain tumor segmentation remains a challenging task, because differentiating brain tumors from normal tissues is difficult, tumor boundaries are often ambiguous and there is a high degree of variability in the shape, location, and extent of the patient. It is therefore desired to devise effective image segmentation architectures. In the past few decades, many algorithms for automatic segmentation of brain tumors have been proposed. Methods based on deep learning have achieved favorable performance for brain tumor segmentation. In this article, we propose a Multi-Scale 3D U-Nets architecture, which uses several U-net blocks to capture long-distance spatial information at different resolutions. We upsample feature maps at different resolutions to extract and utilize sufficient features, and we hypothesize that semantically similar features are easier to learn and process. In order to reduce the computational cost, we use 3D depthwise separable convolution instead of some standard 3D convolution. On BraTS 2015 testing set, we obtained dice scores of 0.85, 0.72, and 0.61 for the whole tumor, tumor core, and enhancing tumor, respectively. Our segmentation performance was competitive compared to other state-of-the-art methods.     

Dynamical modelling of haematopoiesis: an integrated view over the system in homeostasis and under perturbation

A very high number of different types of blood cells must be generated daily through a process called haematopoiesis in order to meet the physiological requirements of the organism. All blood cells originate from a population of relatively few haematopoietic stem cells residing in the bone marrow, which give rise to specific progenitors through different lineages. Steady-state dynamics are governed by cell division and commitment rates as well as by population sizes, while feedback components guarantee the restoration of steady-state conditions. In this study, all parameters governing these processes were estimated in a computational model to describe the haematopoietic hierarchy in adult mice. The model consisted of ordinary differential equations and included negative feedback regulation. A combination of literature data, a novel divide et impera approach for steady-state calculations and stochastic optimization allowed one to reduce possible configurations of the system. The model was able to recapitulate the fundamental steady-state features of haematopoiesis and simulate the re-establishment of steady-state conditions after haemorrhage and bone marrow transplantation. This computational approach to the haematopoietic system is novel and provides insight into the dynamics and the nature of possible solutions, with potential applications in both fundamental and clinical research.     

A utility-driven approach to supplier evaluation and selection: empirical validation of an integrated solution framework

Supplier evaluation and selection (SES) problems have long been studied, leading to the development of a wide range of individual and hybrid models for solving them. However, the lack of widespread diffusion of existing SES models in the industry points to a need for simpler models that can systematically evaluate both qualitative and quantitative attributes of potential suppliers while enhancing the flexibility decision-makers need to account for relevant situational factors. Furthermore, empirical validations of existing models in SES have been few and far between. With a view to addressing these issues, this paper proposes an integrated solution framework that can be used to evaluate both tangible and intangible attributes of potential suppliers. The proposed framework combines three individual methods, namely the fuzzy analytic hierarchy process, fuzzy complex proportional assessment and fuzzy linear programming. The framework is validated through application in a Turkish textile company. The results generated using the proposed framework is compared with the actual historical data collected from the company. Additionally, a feasibility assessment is conducted on the sample supplier selection criteria employed, as well as assessment of the results generated using the proposed model.     

An evolutionary approach to facilitating organisational learning: an experiment by the Christian Commission for Development in Bangladesh

A participatory monitoring system was devised in the course of developing an evolutionary perspective on learning within organisations and in co-operation with the Christian Commission for Development in Bangladesh (CCDB). In this approach, indicators are abandoned: instead the method focuses on the identification of significant change as perceived and interpreted by the various participants. It relies on the use of qualitative information. It extracts meaning out of events that have taken place rather than making assumptions about future events. The system has been valuable to CCDB and has been expanded since its first conception.     

A formal approach to the integrated analysis of security and QoS

Concurrent and distributed systems are subject to several requirements of different nature. Among them security and quality of service (QoS) are two fundamental aspects, which can have a profound impact on the system performability. Unfortunately, the study of the tradeoff between security guarantees and performance needs is hard to accomplish, because the related analysis activities are usually carried out separately. In this paper, we present an integrated and tool-supported methodology encompassing both activities, which can provide insights about how to trade the QoS delivered by a system with its security guarantees. The methodology is illustrated by assessing the effectiveness and the efficiency of the securing strategy implemented in the NRL Pump, a trusted device proposed to secure the replication of information from a low-security level enclave to a high-security level enclave.     

An integrated approach to the vehicle routing and container loading problems

Real-world distribution problems raise some practical considerations that usually are not considered in a realistic way in more theoretical studies. One of these considerations is related to the vehicle capacity, not only in terms of cubic meters or weight capacity but also in terms of the cargo physical arrangements. In a distribution scene, two combinatorial optimization problems, the vehicle routing problem with time windows and the container loading problem, are inherently related to each other. This work presents a framework to integrate these two problems using two different resolution methods. The first one treats the problem in a sequential approach, while the second uses a hierarchical approach. To test the quality and efficiency of the proposed approaches, some test problems were created based on the well-known Solomon, Bischoff and Ratcliff test problems. The results of the integrated approaches are presented and compared with results of the vehicle routing problem with time windows and the container loading problem applied separately.     

Statistical heterospectroscopy, an approach to the integrated analysis of NMR and UPLC-MS data sets: application in metabonomic toxicology studies

Statistical heterospectroscopy (SHY) is a new statistical paradigm for the coanalysis of multispectroscopic data sets acquired on multiple samples. This method operates through the analysis of the intrinsic covariance between signal intensities in the same and related molecules measured by different techniques across cohorts of samples. The potential of SHY is illustrated using both 600-MHz 1H NMR and UPLC-TOFMS data obtained from control rat urine samples (n = 54) and from a corresponding hydrazine-treated group (n = 58). We show that direct cross-correlation of spectral parameters, viz. chemical shifts from NMR and m/z data from MS, is readily achievable for a variety of metabolites, which leads to improved efficiency of molecular biomarker identification. In addition to structure, higher level biological information can be obtained on metabolic pathway activity and connectivities by examination of different levels of the NMR to MS correlation and anticorrelation matrixes. The SHY approach is of general applicability to complex mixture analysis, if two or more independent spectroscopic data sets are available for any sample cohort. Biological applications of SHY as demonstrated here show promise as a new systems biology tool for biomarker recovery.     

An integrated approach to the optimization of in-plant wastewater interception with mass and property constraints

This article addresses the problem of in-plant pollution prevention for processes with multiple streams, containing pollutants and environmentally undesirable properties through mass exchange networks (MEN). In-plant interception is used to adjust the concentrations and properties of the wastewater streams. A pinch-based disjunctive-optimization approach is adopted. The determination of the pinch point (being the most constrained thermodynamic and practical operating condition) is critical for determination of optimum design conditions. The selection of the appropriate mass separating agent(s) (MSAs) is based on thermodynamic and economic considerations. A screening procedure modeled through mathematical programming is developed with disjunctive constraints to screen alternatives and invoke the proper models when a certain technology is to be utilized. A case study is solved to illustrate the proposed approach.     

Finite element approach toward an advanced understanding of deep rolling induced residual stresses,and an application to railway axles

A full-scale railway axle, made of medium strength steel EA4T and adopted for high-speed applications, is deep rolled. The induced residual stresses were experimentally characterized by X-ray diffraction and hole drilling. A realistic finite element model is proposed to overcome some of the existing shortcomings in simulation of deep rolling. Deep rolling coverage is defined, formulated and incorporated into the simulation. The model is validated by the experimental measurements. A parametric study is performed to investigate the effect of rolling force (4–19 kN), rolling feed (0.1–0.7 mm/rev) and roll geometry (1.5–10 mm roll tip radius) on the distribution of residual stresses and the induced hardening. A fatigue crack propagation algorithm is used to analyze the influence of the technological parameters on the lifetime of railway axles. Lower feeds, higher loads and thicker rolls, all resulting in higher coverage, can result in higher improvement against fatigue crack propagation. However, extremely high coverage can deteriorate the performance of deep rolled components. Coverage can effectively serve as a master parameter in deep rolling. As a general rule of thumb, adopting deep rolling feed to get a coverage level of 500–900%, while avoiding too high rolling loads and too thin rolls, can induce a suitable compressive residual stress distribution; and effectively prevent/retard fatigue crack propagation.     

An integrated approach to the optimum utilization of national tungsten resources: Technology gaps

A critical review of the current status of tungsten resources, of state-of-the-art processing technology and of product development in India vis-a-vis the world scenario is presented. An attempt has been made to identify technology gap areas requiring attention.     

Blood flow and coherent vortices in the normal and aneurysmatic aortas: a fluid dynamical approach to intra-luminal thrombus formation

Abdominal aortic aneurysms (AAAs) are frequently characterized by the development of an intra-luminal thrombus (ILT), which is known to have multiple biochemical and biomechanical implications. Development of the ILT is not well understood, and shear–stress-triggered activation of platelets could be the first step in its evolution. Vortical structures (VSs) in the flow affect platelet dynamics, which motivated the present study of a possible correlation between VS and ILT formation in AAAs. VSs educed by the λ₂-method using computational fluid dynamics simulations of the backward-facing step problem, normal aorta, fusiform AAA and saccular AAA were investigated. Patient-specific luminal geometries were reconstructed from computed tomography scans, and Newtonian and Carreau–Yasuda models were used to capture salient rheological features of blood flow. Particularly in complex flow domains, results depended on the constitutive model. VSs developed all along the normal aorta, showing that a clear correlation between VSs and high wall shear stress (WSS) existed, and that VSs started to break up during late systole. In contrast, in the fusiform AAA, large VSs developed at sites of tortuous geometry and high WSS, occupying the entire lumen, and lasting over the entire cardiac cycle. Downward motion of VSs in the AAA was in the range of a few centimetres per cardiac cycle, and with a VS burst at that location, the release (from VSs) of shear-stress-activated platelets and their deposition to the wall was within the lower part of the diseased artery, i.e. where the thickest ILT layer is typically observed. In the saccular AAA, only one VS was found near the healthy portion of the aorta, while in the aneurysmatic bulge, no VSs occurred. We present a fluid-dynamics-motivated mechanism for platelet activation, convection and deposition in AAAs that has the potential of improving our current understanding of the pathophysiology of fluid-driven ILT growth.     

Optimal indolence: a normative microscopic approach to work and leisure

Dividing limited time between work and leisure when both have their attractions is a common everyday decision. We provide a normative control-theoretic treatment of this decision that bridges economic and psychological accounts. We show how our framework applies to free-operant behavioural experiments in which subjects are required to work (depressing a lever) for sufficient total time (called the price) to receive a reward. When the microscopic benefit-of-leisure increases nonlinearly with duration, the model generates behaviour that qualitatively matches various microfeatures of subjects’ choices, including the distribution of leisure bout durations as a function of the pay-off. We relate our model to traditional accounts by deriving macroscopic, molar, quantities from microscopic choices.     

A dynamic programming approach to integrated assembly planning and supplier assignment with lead time constraints

As manufacturers face fierce competition in the global market, responsiveness has become an important competitiveness factor in addition to quality and cost. One essential responsiveness strategy is to reduce product development and lead times by integrating assembly planning with supplier assignment. This paper addresses the problem of integrated assembly and supply chain design under lead-time constraints by formulating and solving an optimisation problem with minimal total supply chain costs. This new time-constrained joint optimisation problem belongs to an NP-hard resource-constrained scheduling problem. To model this problem effectively, we develop a novel Hyper AND/OR graph and apply it for integrating assembly and supply chain decisions. We also develop a dynamic programming model and associated algorithm in order to solve the integrated optimisation problem with pseudo-polynomial time complexity in practice. Numerical case studies validate that the methods developed can solve the integrated decision-making problem optimally and efficiently. This paper overcomes the limitations of previous studies on concurrent assembly decomposition and supplier selection, which optimises cost without time constraints. The models and results of this research can be applied to a variety of areas including assembly design, maintenance module planning and supply chain restructuring.     

The development of a conceptual model regarding the role of social modelling in safety behaviour: an integrated literature review

Social modelling is a process where an individual observes a model's behaviour and its consequences, leading to a modification of the observer's old behaviours or the acquisition of new behaviours. Even though diverse fields, including transportation and aviation, have reliably found significant results pertaining to the influences of social modelling on behavioural outcomes, there is a lack of research pertaining to social modelling's influences specifically on safety behaviour. This review details the safety issues related to the mechanisms, influences and effects of social modelling as a way to examine the potential that social modelling has in affecting employees’ safety behaviour. The collected research materials aided in the construction of a preliminary conceptual model regarding the effects of social modelling on safety behaviour. Overall, the review provides safety and organisational researchers with information about a gap in the safety literature and a model that can lead to future research to fill that gap.     

Modelling biological behaviours with the unified modelling language: an immunological case study and critique

We present a framework to assist the diagrammatic modelling of complex biological systems using the unified modelling language (UML). The framework comprises three levels of modelling, ranging in scope from the dynamics of individual model entities to system-level emergent properties. By way of an immunological case study of the mouse disease experimental autoimmune encephalomyelitis, we show how the framework can be used to produce models that capture and communicate the biological system, detailing how biological entities, interactions and behaviours lead to higher-level emergent properties observed in the real world. We demonstrate how the UML can be successfully applied within our framework, and provide a critique of UML''s ability to capture concepts fundamental to immunology and biology more generally. We show how specialized, well-explained diagrams with less formal semantics can be used where no suitable UML formalism exists. We highlight UML''s lack of expressive ability concerning cyclic feedbacks in cellular networks, and the compounding concurrency arising from huge numbers of stochastic, interacting agents. To compensate for this, we propose several additional relationships for expressing these concepts in UML''s activity diagram. We also demonstrate the ambiguous nature of class diagrams when applied to complex biology, and question their utility in modelling such dynamic systems. Models created through our framework are non-executable, and expressly free of simulation implementation concerns. They are a valuable complement and precursor to simulation specifications and implementations, focusing purely on thoroughly exploring the biology, recording hypotheses and assumptions, and serve as a communication medium detailing exactly how a simulation relates to the real biology.