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Unlocking and quantifying fundamental biological processes through tissue microscopy requires accurate, in situ segmentation of all cells imaged. Currently, achieving this is complex and requires exogenous fluorescent labels that occupy significant spectral bandwidth, increasing the duration and complexity of imaging experiments while limiting the number of channels remaining to address the study's objectives. We demonstrate that the excitation light reflected during routine confocal microscopy contains sufficient information to achieve accurate, label-free cell segmentation in 2D and 3D. This is achieved using a simple convolutional neural network trained to predict the probability that reflected light pixels belong to either nucleus, cytoskeleton, or background classifications. We demonstrate the approach across diverse lymphoid tissues and provide video tutorials demonstrating deployment in Python and MATLAB or via standalone software for Windows.

Functional principal components define modes of variation in time series, which represent characteristic movement patterns in biomechanical data. Their usefulness however depends on the prior choices made in data processing. Recent research showed that better curve alignment achieved with registration (dynamic time warping) reduces errors in linear models predicting jump height. However, the efficacy of registration in different preprocessing combinations, including time normalisation, padding and feature extraction, is largely unknown. A more comprehensive analysis is needed, given the potential value of registration to machine learning in biomechanics. We evaluated popular preprocessing methods combined with registration, creating 512 models based on ground reaction force data from 385 countermovement jumps. The models either predicted jump height or classified jumps into those performed with or without arm swing. Our results show that the classification models benefited from registration in various forms, particularly when landmarks were placed at critical points. The best classifier achieved a 5.5 percentage point improvement over the equivalent unregistered model. However, registration was detrimental to the jump height models, although this performance variable may be a special case given its direct relationship with impulse. Our meta-models revealed the relative contributions made by various preprocessing operations, highlighting that registration does not generalise so well to new data. Nonetheless, our analysis shows the potential for registration in further biomechanical applications, particularly in classification, when combined with the other appropriate preprocessing operations.

The aims of this study were to establish epidemiology, clinical management and outcomes in cases of adult out-of-hospital cardiac arrest complicated by hyperthermia attended by the London Ambulance Service NHS Trust between January 2018 and December 2019. Where evidence is available in relation to this sub-set of cardiac arrest patients it is generally limited to small case series and we therefore we sought to improve knowledge and target therapeutic interventions.Retrospective analysis of 253 cases was undertaken following abstraction from an established cardiac arrest database. Age ranged from 18-99 years with a median of 72 years (IQR 28) and 53.4% (n = 135) of patients were female. Overall thirty-day mortality was 94.5% (n = 239), with 48.2% (n = 122) of patients recognised life extinct in the out-of-hospital phase following termination of resuscitation. No significant differences in clinical characteristics stratified according to temperature group were identified. The presumed aetiology was infective in 62.8% (n = 159) of patients, and due to drug ingestion or heat illness in 7.5% (n = 19) and 2% (n = 5) respectively. In the remaining cases (27.7%, n = 70) it was not possible to determine the likely cause of the arrest.Previous research relating to cardiac arrest complicated by hyperthermia is limited to case reports and small case series, suggesting that the current study represents the most comprehensive analysis of this sub-group of out-of-hospital cardiac arrest patients currently available. Most cases were associated with evidence of infection compared with drug related aetiologies and heat illness. Where indicated, cooling was applied infrequently using inconsistent methods.

Gene expression is regulated by a complex transcriptional network. It is of interest to quantify uncertainty of not knowing accurately reaction rates of underlying biochemical reactions, and to understand how they affect gene expression. Assuming a kinetic model of the lac circuit in Escherichia coli, regardless of how many reactions are involved in transcription regulation, transcription rate is shown to be the most important parameter affecting steady state production of mRNA and protein in the cell. In particular, doubling the transcription rate approximately doubles the number of mRNA synthesized at steady state for any rates of transcription inhibition and activation. On the other hand, increasing the rate of transcription inhibition by 10% reduces the average steady state count of mRNA by about 7%, whereas changes in the rate of transcription activation appear to have no such effect. Furthermore, for wide range of reaction rates in the kinetic model of the lac genetic switch considered, protein production was observed to always reach a maximum before the degradation reduces its count to zero, and this maximum was found to be always at least 27 protein molecules. Such value appears to be a fundamental structural property of genetic circuits making it very robust against changes in the internal and external conditions.

In the United Kingdom (UK) the prison population has increased by around one third since the turn of the millennium amid growing concern over the correctional mission of prisons, the number of prisoners exhibiting mental health difficulties and high levels of recidivism. This study aims to explore the relationship between 'imported' (pre-prison) factors and prisoner mental health status. Prisoners (N = 756) from two UK prisons completed an established measure of mental health (General Health Questionnaire: GHQ-12) and a bespoke survey on pre-prison characteristics and experiences (for example, dispositions, childhood abuse, substance misuse, learning difficulties and employment). Prevalence of mental health difficulties was high, with 40.3% reaching the 'caseness' threshold. Binary logistic regression and odds ratio analyses were used to explore the ability of imported factors to predict mental health 'caseness' and the direction of influence. Collectively, the imported factors correctly predicted the caseness category of 76.5% of participants (p .001). Pre-prison dispositions proved to be strong predictors of caseness as did childhood sexual abuse and learning difficulties at school. We found the direction of influence of three imported factors differed from all others: unemployment, prior experience of prison and a history of substance misuse. These three factors are associated with a lower rate of mental health caseness. It is of concern that, on release, these same factors are likely to militate against re-integration into society. Imported factors can serve as powerful predictors of 'within-prison' mental health status, but practitioners need to be cognisant of the relative importance and direction of influence of factors, as evidenced by these findings.

Introduction Soluble copper that can be acquired by bacteria is toxic and therefore antimicrobial. Whether nanostructured copper materials, in either disperse or agglomerated form, have antimicrobial impact, aside from that of their dissolution products, is not clear and was herein addressed. Methods We took five nanostructured copper materials, two metallic, and three oxo-hydroxides with one of these being silicate-substituted. Four agglomerated in the bacterial growth media whilst the silicate-substituted material remained disperse and small (6.5 nm diameter). Antibacterial activity against E. coli was assessed with copper phase distribution measured over time. Using the dose of soluble copper, and benchmark dose non-linear regression modelling, we determined how well this phase predicted antimicrobial activity. Finally, we used Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) analysis to investigate whether membrane adhesion effects by copper were plausible or if intracellular uptake most likely explained the bacterial impact of copper. Results Comparison over time of antimicrobial activity against particulate or soluble phases of the aquated materials clearly demonstrated that soluble copper but not particulate forms were associated with inhibition of bacterial growth. Indeed, the benchmark dose modelling showed the soluble dose required to cause a 50% reduction in E. coli growth was strongly clustered – for all particle formulations – at 14.5 mg/L (10–19 mg/L 90% confidence interval). By comparison, total copper levels associated with the same reduction in viability varied widely (45–549 mg/L). Finally, in favour of this soluble product dominance in terms of antimicrobial activity, copper had low association with bacterial membrane (something both soluble and particulate materials could do) but showed high intra-bacterial levels (something only soluble copper could do). Conclusion Taken together our data show that it is the uptake of soluble but not particulate copper, and the intracellular loading not just contact and membrane association, that drives copper toxicity to bacteria. Therapeutic strategies for novel antimicrobial copper compounds should consider these findings.

This paper discusses a new mathematical model for community-driven disaster planning that is intended to help decision makers exploit the synergies resulting from simultaneously considering actions focusing on mitigation and efforts geared toward long-term recovery. The model is keyed on enabling long-term community resilience in the face of potential disasters of varying types, frequencies, and severities, and the approach's highly iterative nature is facilitated by the model's implementation in the context of a decision support system. Three examples from Mombasa, Kenya, East Africa, are discussed and compared in order to demonstrate the advantages of the new mathematical model over the current ad hoc mitigation and long-term recovery planning approaches that are typically used. Our DSS math model plans for risks from multiple, perhaps concurrent, hazard sources.The DSS model examines dependencies arising under a multi-hazard planning model.Unlike any other models, we include both long-term mitigation and recovery strategies.We compare our model with two previous approaches to show benefits of our method.

The Northridge earthquake of 1994 displaced almost 10,000 families and destroyed major transportation infrastructure within Southern California, and Hurricane Katrina created the largest national housing crisis since the Dust Bowl of 1930, destroying over 300,000 homes and leaving over one million people seeking shelter. Numerous smaller disasters each year such as tornados, costal or inland flooding, and less severe earthquakes also destroy homes and displace families, although on a much smaller scale. Arranging housing for disaster victims ranks as a top priority after the immediate needs for food and medical care are met. This task becomes more challenging as families are displaced for a longer period of time due to increases in costs, government involvement, and expectations of the victims. In early 2009, FEMA released the first-ever National Disaster Housing Strategy which calls for improved planning and outlines the key principles and policies guiding disaster sheltering, interim housing, and restoration of permanent housing. While all three housing problems are very difficult, the provision of adequate temporary or interim housing is perhaps the most challenging. A few researchers have addressed the issue of optimal allocation of temporary housing, but have focused primarily on the first part of the problem which focuses on the selection of adequate capacity from among available interim housing alternatives. The second part of the problem, which consists of recommending housing alternatives to individual families from the pool of temporary housing units selected in phase one such that educational, healthcare, and socio-economic needs are met, has not yet been addressed to the best of our knowledge. We propose a decision support system for assigning families to housing units which addresses these needs. We develop a benchmark integer programming model for developing a balanced housing plan, and then use the model to evaluate three heuristics which could be practically applied with our system. We use a prototypical example to illustrate the model and evaluate the heuristics, and to demonstrate their appropriateness for the development of realistic real-time housing recommendations. We model the recommendation of housing alternatives to disaster victims.Our goal is to minimize distance to socio-economic support structure.Heuristics are developed to allow for real-time support.The best heuristic uses a weighted preference between distance and housing size.We use this heuristic as the foundation of a decision support system.

Summary How cells correct deviations from a mean cell size at mitosis remains uncertain. Classical cell-size homeostasis models are the sizer, timer, and adder [ 1 ]. Sizers postulate that cells divide at some threshold size; timers, that cells grow for a set time; and adders, that cells add a constant volume before division. Here, we show that a size-based probabilistic model of cell-size control at the G2/M transition (P(Div)) can generate realistic cell-size homeostasis in silico. In fission yeast cells, Cyclin BCdc13 scales with size, and we propose that this increases the likelihood of mitotic entry, while molecular noise in its expression adds a probabilistic component to the model. Varying Cdc13 expression levels exogenously using a newly developed tetracycline inducible promoter shows that both the level and variability of its expression influence cell size at division. Our results demonstrate that as cells grow larger, their probability of dividing increases, and this is sufficient to generate cell-size homeostasis. Size-correlated Cdc13 expression forms part of the molecular circuitry of this system.

While many IT security incidents result in relatively minor operational disruptions or minimal recovery costs, occasionally high-impact security breaches can have catastrophic effects on the firm. Unfortunately, measuring security risk and planning for countermeasures or mitigation is a difficult task. Past research has suggested risk metrics which may be beneficial in understanding and planning for security incidents, but most of these metrics are aimed at identifying expected overall loss and do not directly address the identification of, or planning for, sparse events which might result in high-impact loss. The use of an upper percentile value or some other worst-case measure has been widely discussed in the literature as a means of stochastic optimization, but has not been applied to this decision domain. A key requirement in security planning for any threat scenario, expected or otherwise, is the ability to choose countermeasures optimally with regard to tradeoffs between countermeasure cost and remaining risk. Most of the planning models in the literature are qualitative, and none that we are aware of allow for the optimal determination of these tradeoffs. Therefore, we develop a model for optimally choosing countermeasures to block or mitigate security attacks in the presence of a given threat level profile. We utilize this model to examine scenarios under both expected threat levels and worst-case levels, and develop budget-dependent risk curves. These curves demonstrate the tradeoffs which occur if decision makers divert budgets away from planning for ordinary risk in an effort to mitigate the effects of potential high-impact outcomes.

A rheometrical investigation of incipient clots formed in fibrin-thrombin gels is reported in which the Gel Point (GP) is characterised by frequency independence of the loss tangent in small amplitude oscillatory shear measurements over a wide range of thrombin concentration. Values of the fractal dimension (Df) of the GP network calculated from measurements are consistent with those reported in simulations of diffusion limited cluster–cluster aggregation (DLCCA) and reaction limited cluster–cluster aggregation (RLCCA), but differ insofar as the values of Df calculated from the present experiments increase progressively with a reduction in gel formation time. A molecular dynamics simulation (MDS) of systems of rod-like particles was designed to (i) test the hypothesis that the presence of an activation profile in a cluster aggregation model could account for the trend of Df as a function of gel formation time observed experimentally in fibrin-thrombin gels and whole heparinised blood without recourse to the inclusion of fibrinogen-specific interactions; and (ii) to explore the effect of monomer activation kinetics on the microstructure of fractal clusters formed in systems of rigid rod-like particles. The results identify two possible mechanisms for the increase in Df as the gel formation time decreases, both being a consequence of altering the evolution of the clustering dynamics by a process referred to herein as activation limited aggregation (ALA). This ALA-based MDS substantiates the experimental findings by confirming the trend evident in the formation of incipient clots in fibrin-thrombin gels and in whole heparinised blood. A mechanism for ALA involving the aggregation of pre-GP sub-clusters is proposed.

Security countermeasures help ensure the confidentiality, availability, and integrity of information systems by preventing or mitigating asset losses from Cybersecurity attacks. Due to uncertainty, the financial impact of threats attacking assets is often difficult to measure quantitatively, and thus it is difficult to prescribe which countermeasures to employ. In this research, we describe a decision support system for calculating the uncertain risk faced by an organization under cyber attack as a function of uncertain threat rates, countermeasure costs, and impacts on its assets. The system uses a genetic algorithm to search for the best combination of countermeasures, allowing the user to determine the preferred tradeoff between the cost of the portfolio and resulting risk. Data collected from manufacturing firms provide an example of results under realistic input conditions.

Internet markets allow online sellers to rapidly update prices. By employing intelligent software agents known as pricebots, the re-pricing process can be streamlined and automated. Developing the pricebot re-pricing logic requires an understanding of the optimal pricing strategy in relation to competitors' strategies. We use simulation to construct a decision table of the most effective counterstrategy for several competitor strategy combinations. We then design a neural network for classifying the strategies of the competition, which allows us to look up the optimal counterstrategy in the decision table. Our findings indicate that a pricebot armed with the decision table and neural network classifier can recognize when the market is such that no entrant can gain a profit advantage beyond the profit achieved at a common price floor, and in other cases where higher profits are possible, the agent is able to achieve statistically significant profit improvements over the no-pricebot case.

We have calculated the optical structure of wurtzite ZnO doped with Silicon (Si). The calculations are based on the density functional theory with the generalized gradient approximation (GGA) and the projector augmented wave pseudopotentials. The GGA with the Perdew Burke Ernzerhof exchange-correlation functional are employed in the simulations. Ultrasoft pseudopotentials are utilized for the geometry optimization to render the computations tractable as well as to enhance the efficiency. We investigate two kinds of defects in ZnO, namely the substitution of Zn by Si and O by Si. The optical properties, including dielectric function, reflectivity and absorption coefficient of wurtzite ZnO are calculated. The variation in the band gap and energetics have been validated against published results. The dielectric properties follow a steep decreasing trend for the low energy level. In addition, the reflectivity and absorption coefficients reduce abruptly due to the doping.

Cross-sectional scanning tunneling microscopy is used to study defects on the surface of semiconductor laser devices. Step defects across the active region caused by the cleave process are identified. Curved blocking layers used in buried heterostructure lasers are shown to induce strain in the layers above them. Devices are also studied whilst powered to look at how the devices change during operation, with a numerical model that confirms the observed behavior. Whilst powered, low-doped blocking layers adjacent to the active region are found to change in real time, with dopant diffusion and the formation of surface states. A tunneling model which allows the inclusion of surface states and tip-induced band bending is applied to analyze the effects on the tunneling current, confirming that the doping concentration is reducing and defect surface states are being formed.

A technique to generate random fractal aggregates where the fractal dimension is fixed a priori is presented. The algorithm utilizes the box-counting measure of the fractal dimension to determine the number of hypercubes required to encompass the aggregate, on a set of length scales, over which the structure can be defined as fractal. At each length scale the hypercubes required to generate the structure are chosen using a simple random walk which ensures connectivity of the aggregate. The algorithm is highly efficient and overcomes the limitations on the magnitude of the fractal dimension encountered by previous techniques.

High-speed, wireless communication networks are increasing in popularity; however they can be costly and difficult to plan. In this paper we present a spatial decision support system that incorporates expert knowledge of wireless communications, area topography, demographics and propensity to pay for service in order to aid wireless network planners determine optimal placement of equipment to maximize profit or minimize cost. Moreover, the system can be useful in performing policy analysis to determine pricing, governmental subsidy levels, etc. By integrating a GIS tool into the DSS, planners can easily adjust parameters to better understand the problem at hand and move toward bringing broadband connectivity to the last mile.

This paper discusses an automated process of merging conflicting information from disparate sources into a combined knowledge base. The algorithm provided generates a mathematically consistent, majority-rule merging by assigning weights to the various sources. The sources may be either conflicting portions of a single knowledge base or multiple knowledge bases. Particular attention is paid to maintaining the original rule format of the knowledge, while ensuring logical equivalence. This preservation of rule format keeps the knowledge in a more intuitive implication form as opposed to a collection of clauses with many possible logical roots. It also facilitates tracking using the support for each deductive result so that final knowledge in rule form can be ascribed back to original experts. As the approach is fairly involved mathematically, an automated procedure is developed.

This paper considers high performance motion control systems for the Azimuth axis of a 2.4m Altitude-Azimuth telescope manufactured by Telescope Technologies Limited (TTL). Tracking performance is paramount and the telescope is designed to operate with no surrounding enclosure; wind disturbances that could degrade the tracking performance are a major consideration. Previous robust control designs have used a single-input-single-output (SISO) architecture for position tracking, and this paper will assess the stability and performance of a multi-input-multi-output (MIMO) controller using simulations and test data from the real telescope. Simulations indicate that the MIMO design offers better wind disturbance rejection, and the test data show that the implementation of a MIMO control architecture is feasible.

This paper examines the feasibility and worthiness of a sequential simulation optimization strategy using nonparametric metamodeling. Incorporating notions advanced in the nonparametric statistics literature, the procedure starts with a uniform grid of points, and then adds points based on the solution of a mathematical programming problem involving quantiles of the squared second derivative of a thin-plate spline metamodel. Termination is reached based on two user-specified criteria.A feasibility study is conducted, generating 21,000 nonparametric metamodels to fit seven different, basic simulation surfaces. The appropriateness of metamodel fits is judged using recently published criteria. It is concluded that the nonparametric thin-plate spline sequential procedure faithfully reproduces the test case response surfaces and terminates reasonably. However, it is also seen that misleading results may be obtained in systems heavily constrained by budget, and that splines may do a poor job fitting plateaus due to their inherent predisposition to "create ripples."

Numerical simulations are undertaken to optimise the contrast ratios of terahertz optical asymmetric demultiplexer (TOAD) devices subject to frequency-detuned signal and control picosecond optical pulses. Optimum control pulse widths and pulse energies as well as optimum small-signal gains of semiconductor optical amplifiers (SOAs) are identified for achieving maximum contrast ratios in TOAD devices.

This paper is part of a research stream whose purpose is to study the effect of simulation response surface behavior on the choice of appropriate simulation optimization search technique. This paper's research lays some groundwork by examining the behavior of simulation response surfaces themselves. The point here is not to criticize existing simulation-optimization techniques (such as Response Surface Methodology (RSM). Rather, one point is to emphasize the care and precision that must be used to invoke extant procedures properly, while another is to demonstrate the need for additional methods such as nonparametric approaches. In particular, this paper examines a simple, inventory-simulation model under various experimental conditions, including some factors under a user's control, and some not. Both point and region estimates of surface characteristics are determined and graphed while such factors as number of replications, simulation run length, and demand and lead-time variances are varied. It is found, for example, that even for this simple surface such optimization techniques as first-order RSM can be inappropriate over 21–98% of the feasible region, depending on the case. Four implications are noted from the research: the care that should be exercised with existing simulation-optimization techniques; the need for a simulation-optimization starter; the importance of examining global, nonparametric-metamodeling approaches to simulation optimization; and the desirability of investigating a multi-strategy approach to optimization. The paper concludes with a call for further research investigating these suggestions.

We have investigated the mechanism of stimulated emission in ZnCdSeZnSSe quantum wells through measurements of the optical gain spectrum between 77 and 270 K. We also calculated the optical gain using a model which included many-body effects and found excellent agreement with our measurements. Our results are inconsistent with an excitonic gain mechanism and we conclude that the stimulated emission arises from an electron—hole plasma in our samples. However, we find that the electron-hole Coulomb interaction is still significant at room temperature in II–VI heterostructures.

This research introduces the use of an artificial-intelligence based technique, genetic algorithms (GA), to solve mixed-model assembly-line sequencing problems. This paper shows how practitioners can comfortably implement this approach to solve practical problems. A substantial example is given for which GA produces a solution in just a matter of seconds that improves upon Toyota's Goal Chasing Algorithm. The new method is then investigated on a test bed of 80 problems. Results indicate GA generates an improved sequence over Goal Chasing on 50 of the problems and also shows a performance advantage of 2% across all 80 problems using Toyota's variability of parts consumption criterion. The paper concludes that further investigation to fine tune the GA methodology is warranted. It also points out that the GA approach can readily be used by practitioners to address a variety of managerial goals concurrently, such as inventory and work load equalization.

We have carried out measurements of the internal losses in a multiple quantum well laser of Cd 0.28 Zn 0.72 Se ZnSe . From the dependence of the slope efficiency as a function of cavity length the loss value obtained for the 40 A well width with 5 wells in the sample is 50 cm−1. This very large value is attributed mainly to absorption in the GaAs substrate on which the quantum wells were grown. This measurement shows the importance of using waveguide structures in order to obtain low threshold conditions in II–VI lasers.

Corneal ulcers induced by contact lens wear constitute the most serious and worrying adverse effect associated with thisform of ametropic correction. Risks have been shown to be higher for SCL than RGP and for EW than DW. Also in the UK, regardless of the modality of wear, disposable contact lenses have been reported to be associated with a much greater relative risk of ulcerative keratitis than conventional contact lenses. The UK studies, however, are case-control studies from referral centres that may not be representative of primary care contact lens practice, where the bulk of contact lens fitting is carried out. The current investigation was therefore a historical cohort study carried out in four UK contact lens practices representative of the UK mode of practice and geographic distribution. The study reviewed 647 conventional daily SCL wearers with a mean wearing time of 1.97 years and 780 disposable daily SCL wearers with a mean length of wear of 1.45 years. The results obtained lead to the following conclusions: the annualised corneal ulcer incidence rates were 1.10% for conventional daily wear soft contact lenses and 0.88% for Acuvue disposable contact lenses worn on a daily wear basis. The annualised incidence rates for corneal ulcers that might have been microbial in origin were 0.39% for conventional DW and 0.18% for disposable DW. With conventional DW, none of the ulcers encountered were central; four were paracentral and the remaining 10 were peripheral. The clinical picture observed suggests that the majority of the ulcers were not of a microbial origin, but self-limiting ‘sterile’ peripheral ulcers of yet unknown aetiology. By not differentiating ulcers by type/origin, other researchers may have substantially overestimated the true risk of contact lens related microbial keratitis. The results of this study seem to support the findings of similar studies carried out in other European countries, whereby DW with disposable contact lenses carries a similar or lower risk of keratitis than conventional DW.

Background: Despite advances in resuscitation medicine, survival rates to discharge following out-of-hospital cardiac arrest (OHCA) remain poor. Recent data support early critical care intervention...

Research in the field of urban police patrol-car analysis has tended to concentrate in the areas of vehicle deployment, fleetsize and location, etc., with very little emphasis in the area of vehicle maintenance and replacement policy. As such, the purpose of this paper is to develop and demonstrate a simulation model for patrol-vehicle replacement and maintenance analysis. The simulation model will encompass a Markov-type framework of state movements where the states represent the various stages of a patrol vehicle's life from new to inoperable. The model will be developed in the form of a Q-Gert network, and, demonstrated via a case example of an urban patrol fleet of 100 vehicles.

This study provides information as to general nature, hardware requirements, price and range of applications of approximately 20 simulation software packages. In addition, more detailed information on the use, documentation, etc., of GPSS/PC, SIMAN, PC SIMSCRIPT II.5 and SLAM II PC is included.