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Many animals locate food, mates and territories by following plumes of attractive odors. There are clear differences in the structure of this plume-tracking behavior depending on whether an animal is flying, swimming, walking or crawling. These differences could arise from different control rules used by the central nervous system during these different modes of locomotion or one set of rules interacting with the different environments while walking on the surface versus flying or swimming. Flow speeds and turbulence that characterize the environments where walking and flying insects track plumes may alter the structure of odor plumes in an environment-specific way that results in the same control rules generating behaviors that appear quite different. We tested these ideas by challenging walking male cockroaches, Periplaneta americana, and flying male moths, Manduca sexta, to track plumes of their species' sex pheromones in low wind speeds characteristic of cockroach experimental environments, higher wind speeds characteristic of moth experimental environments, and conditions ranging from low to high turbulence. Introducing a turbulence-generating structure into the flow significantly improved the flying plume tracker's ability to locate the odor source, and changed the structure of the behavior of both flying and walking plume trackers. Our results support the idea that plume trackers moving slowly along the substrate may use the spatial distribution of odor, while faster moving flying plume trackers may use the timing of odor encounters to steer to locate the source.

In natural environments, bear behavior follows seasonal patterns but the zoo environment differs from the natural environment in several ways, including the presence of zoo visitors. Although typically difficult to disentangle, we were able to tease apart the effects of seasonal changes and visitor density on the visibility and behavior of 10 bears representing five species housed at Cleveland Metroparks Zoo due to the disruption caused by COVID-19. We conducted a longitudinal bear behavior monitoring project from June, 2017-November, 2020. Bears were more visible in the spring and in the presence of visitors, locomoted more and were less inactive when large crowds were present, foraged and locomoted more when it was earlier in the day, and locomoted more at higher temperatures. There were limited differences in bear visibility to observers between 2020 (when the zoo was temporarily closed to visitors) and the previous three years. There were no differences in rates of stereotypy or social behavior across seasons, crowds, or daily attendance categories. Based on these limited differences, neither season nor visitor density seemed to have an apparent effect on bear behavior or welfare.

Distributed acoustic sensing (DAS) is a rapidly evolving fiber-optic sensing technology that converts any standard fiber-optic cable into a distributed sensor capable of measuring acoustic events every meter over large (100 km+) distances. We describe a conveyance-agnostic DAS system for vertical seismic profiling (VSP) that has the capability to sense either single- or multi-mode sensing fibers, and encode all auxiliary seismic source signals directly onto the optical data stream using a series of piezo-electric fiber stretchers in-line with the sensing fiber. The DAS system can operate with latency-free synchronization via wireless telemetry between the seismic source controller and the DAS unit in either master or slave modes. Similar to geophone-based VSP data acquisition systems, the time-break signal is used to trigger data acquisition to ensure precise time synchronization at sub-millisecond accuracy between the DAS system and the seismic source. The system enables effective data management and the real-time generation of 1 millisecond sampled seismic and navigation data that conforms to the industry-standard seismic data formats, thus eliminating any latency between acquisition and field data deliverables.

BackgroundA contemporary understanding of disability evolution in multiple sclerosis (MS) is an essential tool for individual disease management and planning of interventional studies. We have used prospectively collected longitudinal data to analyse disability progression and variation in a British MS cohort.MethodsCox proportional hazards regression was used to estimate hazard of Expanded Disability Status Scale (EDSS) 4.0 and 6.0. A continuous Markov model was used to estimate transitional probabilities for individual EDSS scores. Models were adjusted for age at MS onset, sex and disease-modifying treatments (DMTs) exposure.Results2135 patients were included (1487 (70%) female, 1922 (89%) relapsing onset). 865 (41%) had used DMTs. Median time to EDSS 4.0 and 6.0 was 18.2 years (95% CI 16.3 to 20.2) and 22.1 years (95% CI 20.5 to 24.5). In the Markov model, the median time spent at EDSS scores of ConclusionsThese data provide a detailed contemporary model of disability outcomes in a representative population-based MS cohort. They support a trend of increasing time to disability milestones compared with historical reference populations, and document disability variation with the use of transitional matrices. In addition, they provide essential information for patient counselling, clinical trial design, service planning and offer a comparative baseline for assessment of therapeutic interventions.

In all carbon capture, utilization, and storage (CCUS) projects, monitoring, verification, and accounting is required to span short to long periods to ensure plume extents and geologic integrity meet operational and regulatory objectives. Fiber-optic cables permanently deployed in the completions of injector wells enable time-lapse (4D) vertical seismic profile (VSP) imaging using distributed acoustic sensing (DAS). Most CCUS projects are onshore, and the majority of those utilize supercritical CO2flooding for enhanced oil recovery (EOR). In these cases, fiber-optic installations, acquisition, and analysis are relatively straightforward. Offshore transport and storage projects, whether for EOR or sequestration in saline aquifers, may utilize subsea wells wherein fiber-optic deployment is not as straightforward. Unlike dry-tree wells, DAS of subsea wells requires advanced optical engineering solutions to compensate for the reduced acoustic bandwidth, optical losses, and back reflections accumulated through umbilicals, multiple wet- and dry-mate optical connectors, splices, optical feedthrough systems, and downhole fibers. In this paper, we simulate VSP shot records of a carbon storage site for a variety of proposed subsea DAS concepts and evaluate the 3D and 4D seismic image quality of each using Kirchhoff migration of upgoing seismic wavefields with their expected signal-to-noise ratios. We normalize interrogator performance, so we are evaluating the sensing topology only. We show that a subsea fiber topology consisting of dual transmission fibers, a remote circulator with selective amplification of the backscattered light, and enhanced backscatter sensing fiber results in high-quality seismic images suitable for both 3D and 4D VSPs of carbon storage.

Several recent studies have advanced the use of time-lapse distributed acoustic sensing vertical seismic profile data in horizontal wells for determining hydraulically stimulated fracture properties. Hydraulic fracturing in a horizontal well typically generates vertical fractures in the rock medium around each stage. We have modeled the hydraulically stimulated formation with vertical fracture sets about the lateral wellbore as a horizontally transverse isotropic medium. Rock-physics modeling is used to relate the anisotropy parameters to the fracture properties. This modeling is used to develop an inversion for compressional wave time delay to the fracture height and density of each stage. Field data from two horizontal wells are analyzed, and the fracture height evaluated using this technique is consistent with the microseismic analysis.

We herein report experimental applications of a novel, automated computational approach to chemical reaction network (CRN) identification. This report shows the first chemical applications of an autonomous tool to identify the kinetic model and parameters of a process, when considering both catalytic species and various integer and non-integer orders in the model's rate laws. This kinetic analysis methodology requires only the input of the species within the chemical system (starting materials, intermediates, products, etc.) and corresponding time-series concentration data to determine the kinetic information of the chemistry of interest. This is performed with minimal human interaction and several case studies were performed to show the wide scope and applicability of this process development tool. The approach described herein can be employed using experimental data from any source and the code for this methodology is also provided open-source., We herein report experimental applications of a novel, automated computational approach to chemical reaction network (CRN) identification.

The acetone-butanol-ethanol (ABE) fermentation from corn stover was considered. We propose, study and optimise, via process simulation (using MATLAB® and Aspen Plus®) the use of fermentation tanks-in-series and in situ product recovery by vacuum evaporation. As the operating time of continuous fermentation processes is usually limited at less than 500 h, shutdown and start-up of the reactors are considered and optimised. A multi-objective optimisation methodology that considers economics as well as the energy requirements of the process was used. The optimal configuration was found to be five fermentation tanks-in-series where the first and the last reactors are operated at atmospheric pressure, and the intermediate vessels are operated under vacuum. The economic potential using this configuration was found to be 45% higher than that of vacuum fermenters operating in parallel (continuous operating mode). Also, the total fuel requirements for ABE recovery and purification system were as low as 7 MJ kg−1 butanol, a reduction of between 4 and 33% when compared to a parallel configuration of batch, fed-batch or continuous fermenters. The energy efficiency of this recovery and reaction system was as high as 74% when co-generation is considered.

Late prehistoric and early historic communal hunting sites along the southwestern mountainous margins of the Great Basin, United Sates, include timber-built corral-traps estimated to be only a few ...

Housing affordability has become an increasing challenge for cities in the United States, though the causes vary. Since 1986, the value of the Low Income Housing Tax Credit—the federal government’s primary vehicle for subsidizing the construction and preservation of affordable housing—has struggled even to keep up with inflation. This chapter argues that because the United States’ affordability crisis manifests itself in many different ways, cities and towns need to be proactive in developing and implementing well-tailored local housing strategies, taking advantage of the knowledge and expertise of groups who understand local housing needs and market conditions. It lays out a framework for identifying the best set of programs and policies each locality can and should take. Two case studies—New York City and Singapore—illustrate different approaches to deal with the challenges of providing affordable housing. When addressing affordability challenges, context matters, as evidenced by the difference in approaches between Singapore and New York City.

We herein report a novel kinetic modelling methodology whereby identification of the correct reaction model and kinetic parameters is conducted by an autonomous framework combined with transient flow measurements to enable comprehensive process understanding with minimal user input. An automated flow chemistry platform was employed to initially conduct linear flow-ramp experiments to rapidly map the reaction profile of three processes using transient flow data. Following experimental data acquisition, a computational approach was utilised to discriminate between all possible reaction models as well as identify the correct kinetic parameters for each process. Species that are known to participate in the process (starting materials, intermediates, products) are initially inputted by the user prior to flow ramp experiments, then all possible model candidates are compiled into a model library based on their potential to occur after mass balance assessment. Parallel computational optimisation then evaluates each model by algorithmically altering the kinetic parameters of the model to allow convergence of a simulated kinetic curve to the experimental data provided. Statistical analysis then determines the most likely reaction model based on model simplicity and agreement with experimental data. This automated approach to gaining full process understanding, whereby a small number of data-rich experiments are conducted, and the kinetics are evaluated autonomously, shows significant improvements on current industrial optimisation techniques in terms of labour, time and overall cost. The computational approach herein described can be employed using data from any set of experiments and the code is open-source.

Reliable kinetic models are important for the design and optimisation of lignocellulosic ethanol production. A new kinetic model describing ethanol production using Zymomonas mobilis ZM4(pZB5) that is applicable to single (glucose or xylose) or mixed (glucose and xylose) substrate fermentations is developed. This work extends previous contributions through consideration of an empirical term for the preferential usage of glucose when compared to xylose as well as the prediction of the production rate of xylitol. Kinetic model parameters are obtained through kinetic fitting using experimental data available in the literature (seventeen fermentations in batch or continuous operation). The average coefficient of determination of xylose, xylitol, ethanol, glucose and biomass predictions using the kinetic model developed in this work was 0.984. Furthermore, it is demonstrated that through the inclusion of xylitol production and the inhibition of xylose consumption by xylitol in the kinetic model the productivity of ethanol may be accurately estimated.

ATP is not only an essential metabolite of cellular biochemistry but also acts as a signal in the extracellular milieu. In plants, extracellular ATP is monitored by the purinergic receptor P2K1. Recent studies have revealed that extracellular ATP acts as a damage-associated molecular pattern in plants, and its signaling through P2K1 is important for mounting an effective defense response against various pathogenic microorganisms. Biotrophic and necrotrophic pathogens attack plants using different strategies, to which plants respond accordingly with salicylate-based or jasmonate/ethylene-based defensive signaling, respectively. Interestingly, defense mediated by P2K1 is effective against pathogens of both lifestyles, raising the question of the level of interplay between extracellular ATP signaling and that of jasmonate, ethylene, and salicylate. To address this issue, we analyzed ATP-induced transcriptomes in wild-type Arabidopsis (Arabidopsis thaliana) seedlings and mutant seedlings defective in essential components in the signaling pathways of jasmonate, ethylene, and salicylate (classic defense hormones) as well as a mutant and an overexpression line of the P2K1 receptor. We found that P2K1 function is crucial for faithful ATP-induced transcriptional changes and that a subset of genes is more responsive in the P2K1 overexpression line. We also found that more than half of the ATP-responsive genes required signaling by one or more of the pathways for the classical defense hormones, with the jasmonate-based signaling being more critical than others. By contrast, the other ATP-responsive genes were unaffected by deficiencies in signaling for any of the classical defense hormones. These ATP-responsive genes were highly enriched for defense-related Gene Ontology terms. We further tested the ATP-induced genes in knockout mutants of transcription factors, demonstrating that MYCs acting downstream of the jasmonate receptor complex and calmodulin-binding transcription activators are nuclear transducers of P2K1-mediated extracellular ATP signaling.

Summary▪We augment the well-known susceptible – infected – recovered – deceased (SIRD) epidemiological model to include vaccination dynamics, implemented as a piecewise continuous simulation. We calibrate this model to reported case data in the UK at a national level,▪Our modelling approach decouples the inherent characteristics of the infection from the degree of human interaction (as defined by the effective reproduction number,Re). This allows us to detect and infer a change in the characteristic of the infection, for example the emergence of the Kent variant,▪We find that that the infection rate constant (k) increases by around 89% as a result of the B.1.1.7 (Kent) COVID-19 variant in England,▪Through retrospective analysis and modelling of early epidemic case data (between March 2020 and May 2020) we estimate that ∼1.2M COVID-19 infections were unreported in the early phase of the epidemic in the UK. We also obtain an estimate of the basic reproduction number as,R0= 3.23,▪We use our model to assess the UK Government’s roadmap for easing the third national lockdown as a result of the current vaccination programme. To do this we use our estimated model parameters and a future forecast of the daily vaccination rates of the next few months,▪Our modelling predicts an increased number of daily cases as NPIs are lifted in May and June 2021,▪We quantify this increase in terms of the vaccine rollout rate and in particular the percentage vaccine uptake rate of eligible individuals, and show that a reduced take up of vaccination by eligible adults may lead to a significant increase in new infections.

The intensity values of terrestrial laser scanning (TLS) can be used to reveal painted black rock art behind graffiti and moss. The effect was observed in Gumahon cave in Peñablanca, Philippines where previously unnoticed black pigment was exposed underneath moss, red and white painted graffiti, and etched name graffiti. The application of TLS intensity values for this purpose has not, to our knowledge, been previously reported. The significance of this finding is that archaeologists are provided a new method of detecting obfuscated rock art that can aid interpretation. The method can be applied in similar contexts as black painted rock art is common in limestone caves across Southeast Asia and Micronesia, but also ubiquitous globally.

Flying insects track turbulent odor plumes to find mates, food and egg-laying sites. To maintain contact with the plume, insects are thought to adapt their flight control according to the distribution of odor in the plume using the timing of odor onsets and intervals between odor encounters. Although timing cues are important, few studies have addressed whether insects are capable of deriving spatial information about odor distribution from bilateral comparisons between their antennae in flight. The proboscis extension reflex (PER) associative learning protocol, originally developed to study odor learning in honeybees, was used as a tool to ask if hawkmoths, Manduca sexta, can discriminate between odor stimuli arriving on either antenna. We show moths discriminated the odor arrival side with an accuracy of >70%. Information about spatial distribution of odor stimuli may be available to moths searching for odor sources, opening the possibility that they use both spatial and temporal odor information. This article has an associated First Person interview with the first author of the paper.

Highlights • established chemical engineering modelling practice applied to COVID 19 Re estimation. • effective reproduction number modelled as time varying stoichiometry in kinetic model. • model uses piecewise continuous integration and event and discontinuity management. • nested optimiser algorithm to estimate Re from data with time varying NPIs. • calibration and estimation of non-linear response in Re to NPIs throughout epidemic., Mathematical models are useful in epidemiology to understand COVID-19 contagion dynamics. We aim to demonstrate the effectiveness of parameter regression methods to calibrate an established epidemiological model describing infection rates subject to active, varying non-pharmaceutical interventions (NPIs). We assess the potential of established chemical engineering modelling principles and practice applied to epidemiological systems. We exploit the sophisticated parameter regression functionality of a commercial chemical engineering simulator with piecewise continuous integration, event and discontinuity management. We develop a strategy for calibrating and validating a model. Our results using historic data from 4 countries provide insights into on-going disease suppression measures, while visualisation of reported data provides up-to-date condition monitoring of the pandemic status. The effective reproduction number response to NPIs is non-linear with variable response rate, magnitude and direction. Our purpose is developing a methodology without presenting a fully optimised model, or attempting to predict future course of the COVID-19 pandemic.

Summary Distributed acoustic sensing (DAS) is a rapidly evolving, conveyance-agnostic technology for both seismic and reservoir diagnostic applications. Despite maturity in dry-tree and retrievable applications, there are significant challenges associated with DAS for subsea applications. While fiber optic engineers understand the complexities and subtleties of the sources of optical losses and their respective hardware compensations, very little has been provided to help geoscientists understand the impact of the net signal-to-noise (SNR) impacts on vertical seismic profile (VSP) data, and its 3D and 4D answer products. This is particularly critical to quantify as time-lapse VSP is a primary basis of design for subsea DAS. This paper enumerates the sources of subsea optical signal losses and their respective compensations in different subsea sensing configurations, and then demonstrates their systems-level SNR effects on 3D and 4D VSP imaging relative to the dry-tree base case that geoscientists are familiar with today.

In this paper, we propose a realistic model for gas distribution of an advanced municipal wastewater treatment works and through minimisation of the total cost of gas distribution we perform retrospective optimisation (RO) using historical plant data. This site is the first in the UK with a mixed operational strategy for biomethane produced on site: to burn in combined heat and power (CHP) engines to create electricity, burn in steam boilers for onsite steam use or inject the biomethane into the National Grid. In addition, natural gas can be imported to make up shortfalls in biomethane if required. Implemented using a novel mixed integer linear programming (MILP) approach, to ensure a fast and robust solution, our results indicate the plant operated optimally within accepted tolerance 98% of the time. However, improving plant robustness (such as reducing unexpected breakdown incidents) could yield a significant increase in gas revenue of 7.8%.

This work aims to model, simulate and provide insights into the dynamics and control of COVID-19 infection rates. Using an established epidemiological model augmented with a time-varying disease transmission rate allows daily model calibration using COVID-19 case data from countries around the world. This hybrid model provides predictive forecasts of the cumulative number of infected cases. It also reveals the dynamics associated with disease suppression, demonstrating the time to reduce the effective, time-dependent, reproduction number. Model simulations provide insights into the outcomes of disease suppression measures and the predicted duration of the pandemic. Visualisation of reported data provides up-to-date condition monitoring, while daily model calibration allows for a continued and updated forecast of the current state of the pandemic.

Flying insects track turbulent odor plumes to find mates, food and egg-laying sites. To maintain contact with the plume, insects are thought to adapt their flight control according to the distribution of odor in the plume using the timing of odor onsets and intervals between odor encounters. Although timing cues are important, few studies have addressed whether insects are capable of deriving spatial information about odor distribution from bilateral comparisons between their antennae in flight. The proboscis extension reflex (PER) associative learning protocol, originally developed to study odor learning in honeybees, was modified to show hawkmoths,Manduca sexta, can discriminate between odor stimuli arriving on either antenna. We show moths discriminated the odor arrival side with an accuracy of >70%. The information about spatial distribution of odor stimuli is thus available to moths searching for odor sources, opening the possibility that they use both spatial and temporal odor information.

Summary The pulse repetition rate, and thus sampling frequency, for pulsed distributed acoustic sensing (DAS) systems is inherently limited by the total length of the sensing fiber. For single-fiber, topside interrogation of subsea wells, this is particularly critical as the subsea infrastructure can significantly increase the total sensing fiber length, adversely affecting both sampling frequency and signal-to-noise. We describe how the deployment of a remote circulator in the optical flying lead to the subsea well effectively constrains the sensing fiber to the fiber portion located below the remote circulator. Thus, pulse repetition rates can be increased to match the ones typically achieved for dry-tree wells. Moreover, the fiber topology is immune to back-reflections from infrastructure above the remote circulator, and enables selective amplification of the backscattered light originating from the sensing fiber portion below the remote circulator. The result is a subsea DAS solution that achieves acoustic bandwidth and signal-to-noise performance comparable to dry-tree wells and enables spectral-based DAS processing algorithms developed for sand control, leak detection, inflow profiling, well integrity, and VSP to be straightforwardly applicable to DAS data acquired from subsea wells.

Summary Fiber optic cable conveyance by coiled tubing (CT) broadens the opportunity for vertical seismic profiling (VSP) data acquisition during planned CT interventions. This paper presents a case study of an opportunistic CT distributed acoustic sensing (DAS) VSP acquired simultaneously with the distributed temperature sensing (DTS) warmback survey of a recently stimulated unconventional well. The subsequent VSP processing is shown to overcome the significant noise challenges inherent in CT DAS data, such as persistently strong borehole tube waves induced from the surface operations activities. We present the depth tie between surface seismic and CT DAS VSP derived corridor stack images, demonstrating the viability of CT deployed fiber to opportunistically acquire DAS VSP data.

Summary For real-time seismic data quality control and delivery, distributed acoustic sensing (DAS) systems need to synchronize with the seismic controller. We describe a DAS system that has the ability to encode all auxiliary seismic signals, such as GPS timing, time break signal, vibe sweep, ground force, and hydrophone pressure, directly onto the optical data stream using a series of piezo-electric fiber stretchers in-line with the sensing fiber. Similar to conventional, wireline or permanent geophone VSP data acquisition systems, the time break signal is utilized to trigger data acquisition, which ensures precise time synchronization at sub-millisecond accuracy between the DAS system and the seismic source. The DAS system can operate in either master or slave mode relative to the seismic source, with synchronization via radio or 4G telemetry between the seismic controller and the DAS unit. The system enables effective data management and the real-time generation of 1 ms sampled seismic and navigation data that conforms to the industry-standard SEGY data format; thus eliminating latency between acquisition and field data deliverables.

A kinetic model describing acetone-butanol-ethanol (ABE) production applicable to both single substrate fermentations of glucose and xylose as well as co-fermentation of the substrates has been developed. The model accounts for carbon catabolite repression as well as the inhibition of kinetic rates at high substrate concentrations (∼90 g l−1). Model parameters were obtained through kinetic fitting to previously report experimental data. The model was used to study the design and operation of a continuous ABE fermentation process (with and without recycle of biomass). For continuous operation, it was shown that multiple steady-states exist at low dilution rates. For operation with recycle of biomass, the influence of recycle rate on both biomass concentration and ABE productivity were studied. The results indicate that for a range of recycle and dilution rates, ABE productivity can increase to 16 g l−1 h−1 (10 times higher than that without biomass recycling), consistent with experimental results.