Occupancy Densities Research Articles

Relation between occupation density and ambient noise in open plan offices: a study based on field measurements

Although progress has been made over the last decade on the issue of well-being in open-plan offices, recent surveys show that employees are still dissatisfied with their working environment, particularly the noise environment, remains. However, standards exist to help ensure that open-plan offices are designed to provide the best possible working environment. But, because of the scope of these standards, their recommendations can be contradictory. For example, the French ergonomics standard NF X35-102 makes recommendations on the sizing of workstations, likely to lead to office occupancy densities that are incompatible with the ambient noise level objectives defined in the ISO 22955 standard. To resolve these contradictions, a field measurement protocol was implemented. It consists in (1) a real-time count of the number of people in the office, (2) a measurement of ambient noise, (3) a questionnaire assessing employees' perception of their physical working environment. The data collected in several French companies will make it possible to establish relationships between the ambient noise level, the occupancy density and the perception of noise levels. This paper presents an occupancy sensor developed for this study and measurements of ambient noise level and occupancy ratio during a working day in an open-plan office.

Sensor-based characterization of construction and demolition waste at high occupancy densities using synthetic training data and deep learning.

Sensor-based monitoring of construction and demolition waste (CDW) streams plays an important role in recycling (RC). Extracted knowledge about the composition of a material stream helps identifying RC paths, optimizing processing plants and form the basis for sorting. To enable economical use, it is necessary to ensure robust detection of individual objects even with high material throughput. Conventional algorithms struggle with resulting high occupancy densities and object overlap, making deep learning object detection methods more promising. In this study, different deep learning architectures for object detection (Region-based CNN/Region-based Convolutional Neural Network (Faster R-CNN), You only look once (YOLOv3), Single Shot MultiBox Detector (SSD)) are investigated with respect to their suitability for CDW characterization. A mixture of brick and sand-lime brick is considered as an exemplary waste stream. Particular attention is paid to detection performance with increasing occupancy density and particle overlap. A method for the generation of synthetic training images is presented, which avoids time-consuming manual labelling. By testing the models trained on synthetic data on real images, the success of the method is demonstrated. Requirements for synthetic training data composition, potential improvements and simplifications of different architecture approaches are discussed based on the characteristic of the detection task. In addition, the required inference time of the presented models is investigated to ensure their suitability for use under real-time conditions.

Spatial patterns in occupancy and density of larval lampreys in freshwater habitats restored to a Stage 0 condition

AbstractWe examined occupancy and density of larval lampreys (Entosphenus tridentatus and Lampetra spp.) in two rivers in Oregon (USA) restored to a Stage 0 condition 1–5 years prior, using a multiscale occupancy model and a zero‐inflated Poisson mixture model. We sampled lampreys using backpack electrofishing in randomly distributed, paired, 1‐m2 quadrats and recorded environmental data. Probabilities of occupancy and density were higher when water velocity was low, the substrate was noncompacted, and sediment was dominated by fines (<4 mm). At mean water depth (0.34 m) and velocity (0.09 m/s), estimated densities in occupied quadrats were 4.8 lampreys/m2 (95%: 3.4–6.9) when the substrate was compacted, and fines were not dominant, and 21.1 lampreys/m2 (95%: 17.7–25.3) when the substrate was noncompacted and fines were dominant. Probabilities of detecting occupancy in a 1‐m2 quadrat sampled by backpack electrofishing were 0.76 (95%: 0.64–0.87) when captured after visual observation and 0.80 (95%: 0.71–0.88) with blind sweeps (i.e., constantly moving the net regardless of observation). The probability of capturing a single lamprey in a quadrat sampled by blind sweeps was 0.32 (95%: 0.27–0.37). Sampling in paired 1‐m2 quadrats facilitated concurrent examination of patterns in occupancy and density while accounting for capture probability, which could aid temporal monitoring of restored habitats. To the best of our knowledge, this is the first study to document occupancy and estimate densities of larval lampreys in habitats that underwent valley floor restoration to Stage 0. We observed both lamprey genera within 5 years of restoration. Aquatic restoration that increases low‐velocity, noncompacted, fine sediment habitats could benefit lampreys.

Enhancing Indoor Environmental Quality and Sustainability in Post-Pandemic Office Settings: A Study on Displacement Ventilation Feasibility

The COVID-19 pandemic has catalyzed global efforts toward transitioning to a sustainable society, driving rapid innovation in building technologies, working practices, building design, and whole life cycle environmental impact consideration. In this pursuit, this study explores the enduring impact of these on an alternative ventilation approach for both existing building renovations and new building implementations. Comparing displacement ventilation to mixed-mode ventilation in a Finnish office building with varying occupancy densities, this study examines indoor air quality (IAQ), thermal comfort, total building energy performance, and embodied carbon. The findings reveal that the basic case of mixed ventilation has a specified system primary energy value of 38.83 kWh/m2 (with 28 occupants) and 39.00 kWh/m2 (with 24 occupants), respectively. With the displacement ventilation alternative, it reduces this by 0.3% and 0.1%, enhancing thermal comfort and decreasing turbulence as well as having a marginal decrease in embodied carbon. In general, the study offers three-fold contributions: insights into post-pandemic office mechanical ventilation design with an emphasis on sustainability and ecological footprint considerations, a concrete case study addressing climate action and human-centric IAQ design, and a multifaceted analysis using the Environmental, Social, and Governance (ESG) paradigm, contributing to the groundwork for associated future research and policy progress.

Method of test for CO2-based demand control ventilation systems: Benchmarking the state-of-the-art and the undervalued potential of proportional-integral control

Carbon dioxide (CO2) based demand control ventilation (DCV) adjusts a building’s outdoor air ventilation rate in response to indoor CO2 concentration to save energy while maintaining indoor air quality. Packaged heating, ventilation, and air-conditioning systems often contain DCV controllers with embedded proprietary algorithms that lack transparent performance data. A test method was developed to assess the ability of a DCV controller to maintain the indoor CO2 concentration at a setpoint in response to a series of CO2 generation functions that represent three different building occupancy densities and two occupancy schedules. Six commercially available controllers were tested to demonstrate the method and provide directly comparable results. The performance (in terms of CO2 control and damper movement) of each controller tested was compared to the performance of an ideal controller which knows the CO2 generation function. Finally, the performance of a proportional-integral (PI) controller with preset gains was developed and tested to determine the potential maximum performance achievable with this control strategy. The best performing commercially available controller achieved CO2 control (within 75 ppm of the setpoint) approximately 80 % of the time with damper movement slightly less than an ideal controller. However, most of the commercially available controllers had marginal or poor performance for CO2 control and damper movement. Two controllers had damper movement more than three times the ideal controller. Notably, a PI algorithm configured and tested by the research team achieved superior performance with CO2 control 92 % of the time and damper movement 1.5 times the ideal controller.

Space-Level air conditioner electricity consumption and occupant behavior analysis on a university campus

In China, despite only 2 % of the population residing on university campuses, these campuses account for 8 % of the total energy consumption. Understanding the space-level energy consumption characteristics and energy-related occupant behaviors on a university campus can help improve campus buildings' energy efficiency. This study investigates 21 office spaces on a university campus to better understand the space-level electricity consumption of air-conditioners (AC) and the occupant behaviors (OB), thermal comfort needs, and window operation. First, Internet of Things (IoT) sensors were installed in the 21 office spaces to collect the indoor temperature and humidity, the electricity consumption of the AC, and the status of doors. The data were collected for the entire cooling season. The space-level occupancy patterns were then analyzed based on the quality of the doors, including the first occupant’s arrival time and the last occupant’s departure time. Moreover, the indoor temperature, humidity, and illuminance were combined to evaluate occupants’ thermal and visual comfort need. In addition, statistical and clustering analyses were conducted on air conditioner operations' duration, frequency, and electricity consumption. The results showed that the spaces were typically occupied from 9:21 to 22:25, with 10 h and 53 min daily. The average indoor temperature was 26.1 °C, ranging from 22.1 °C (5th percentile) to 34.9 °C (95th percentile) when the room was occupied and ranging from 21.7 °C (5th percentile) to 32.5 °C (95th percentile) when the AC was on. The air conditioner's electricity consumption ranges from 11.7 to 152.2 kWh/m2 with a median of 68.9 kWh/m2 and from 46.84 to 1883.7 kWh/person with a median of 464.7 kWh/person. The different occupancy densities often lead to a significant difference in the electricity consumption of air conditioners. The findings of this study can be used to support the development of prototype energy models and occupant-centric control (OCC) models for campus office buildings.

Spatio-temporal variability in the strength, directionality, and relative importance of climate on occupancy and population densities in a philopatric mammal, the American pika (Ochotona princeps)

Species distribution models (SDMs) have been widely employed to evaluate species–environment relationships. However, when extrapolated over broad spatial scales or through time, these models decline in their predictive ability due to variation in how species respond to their environment. Many models assume species–environment relationships remain constant over space and time, hindering their ability to accurately forecast distributions. Therefore, there is growing recognition that models could be improved by accounting for spatio-temporal nonstationarity – a phenomenon wherein the factors governing ecological processes change over space or time. Here, we investigated nonstationarity in American pika (Ochotona princeps) relationships with climatic variables in the Rocky Mountains (USA). We first compared broad-scale differences in pika–climate patterns for occupancy and population density across the Southern, Central, and Northern Rockies. Next, we investigated within-ecoregion variation across four mountain ranges nested within the Northern Rockies. Lastly, we tested whether species–climate relationships changed over time within the Central Rockies ecoregion. Across all analyses, we found varying levels of nonstationarity among the climate metrics for both occupancy and density. Although we found general congruence in temperature metrics, which consistently had negative coefficients, and moisture metrics (e.g., relative humidity), which had positive coefficients, nonstationarity was greatest for summer and winter precipitation over both space and time. These results suggest that interpretations from one ecoregion should not be applied to other regions universally – especially when using precipitation metrics. The within-ecoregion analysis found much greater variation in the strength-of-relationship coefficients among the four mountain ranges, relative to the inter-regional analysis, possibly attributable to smaller sample sizes per mountain range. Lastly, the importance of several variables shifted through time from significant to insignificant in the temporal analysis. Our results collectively reveal the overall complexity underlying species–environment relationships. With rapidly shifting conditions globally, this work adds to the growing body of literature highlighting how issues of spatio-temporal nonstationarity can limit the accuracy, transferability, and reliability of models and that interpretations will likely be most robust at local to regional scales. Diagnosing, describing, and incorporating nonstationarity of species–climate relationships into models over space and time could serve as a pivotal step in creating more informative models.

Study of Creeping Discharges Propagating Along a Solid Insulating Surface Immersed in Mineral Oil and Palm Kernel Oil Methyl Ester Under Negative Lightning Impulse Voltage

This article presents the results of an experiment designed to study creeping discharges on a solid insulating surface immersed in palm kernel oil methyl ester (PKOME) compared with those produced from mineral oil (MO). The investigation takes place under standard negative lightning impulse voltage application, and for the three following solid insulating surfaces: hardened glass (HG), porcelain (PO), and simple glass (SG). The distributions of the radial discharge occupancy densities as a function of the thickness of the solid material and the insulating liquid are evaluated. A statistical study of the total and final length of the branches produced by the discharges is presented, as well as the current amplitudes and the charge produced by this phenomenon. A fractal analysis of the phenomenon is also presented. The experimental results show that the distribution of the average radial density of the discharge, the total and final lengths of the branches, and fractal dimension depend strongly on the physicochemical characteristics of the insulation system.

Numerical and Experimental Study on the Indoor Climate in a Classroom with Mixing and Displacement Air Distribution Methods

One main challenge of air distribution in classrooms is to guarantee ventilation performance under different usage conditions. In this study, the indoor climate in summer and winter conditions with different occupancy densities in the classroom is presented. Thermal condition measurements of a half-size classroom were performed in a test room with four air suppliers: wall-grilles, ceiling diffusers, perforated duct diffusers, and displacement ventilation. Those measured data were used for CFD validation of the whole classroom. With CFD simulations, indoor climate parameters with different air diffusers are compared in summer and winter conditions. The results show that displacement ventilation gives the best performance in the occupied zone. The air change efficiency can be reached with displacement ventilation of 1.4 and of only 1 with the other three air diffusers. The air velocities were reasonably low (<0.3 m/s), and the indoor was quite uniform with ceiling diffusers, which is another well-performing solution for classrooms. Corridor wall-grilles give uniform thermal conditions but can have high velocities (0.4 m/s) on the perimeter side of the room space. The air distribution from the perforated duct diffuser is unstable, which causes high local draft (over 20%) in the occupied zone.

Estimating waiting times, patient flow, and waiting room occupancy density as part of tuberculosis infection prevention and control research in South African primary health care clinics.

Transmission of respiratory pathogens, such as Mycobacterium tuberculosis and severe acute respiratory syndrome coronavirus 2, is more likely during close, prolonged contact and when sharing a poorly ventilated space. Reducing overcrowding of health facilities is a recognised infection prevention and control (IPC) strategy; reliable estimates of waiting times and 'patient flow' would help guide implementation. As part of the Umoya omuhle study, we aimed to estimate clinic visit duration, time spent indoors versus outdoors, and occupancy density of waiting rooms in clinics in KwaZulu-Natal (KZN) and Western Cape (WC), South Africa. We used unique barcodes to track attendees' movements in 11 clinics, multiple imputation to estimate missing arrival and departure times, and mixed-effects linear regression to examine associations with visit duration. 2,903 attendees were included. Median visit duration was 2 hours 36 minutes (interquartile range [IQR] 01:36-3:43). Longer mean visit times were associated with being female (13.5 minutes longer than males; p<0.001) and attending with a baby (18.8 minutes longer than those without; p<0.01), and shorter mean times with later arrival (14.9 minutes shorter per hour after 0700; p<0.001). Overall, attendees spent more of their time indoors (median 95.6% [IQR 46-100]) than outdoors (2.5% [IQR 0-35]). Attendees at clinics with outdoor waiting areas spent a greater proportion (median 13.7% [IQR 1-75]) of their time outdoors. In two clinics in KZN (no appointment system), occupancy densities of ~2.0 persons/m2 were observed in smaller waiting rooms during busy periods. In one clinic in WC (appointment system, larger waiting areas), occupancy density did not exceed 1.0 persons/m2 despite higher overall attendance. In this study, longer waiting times were associated with early arrival, being female, and attending with a young child. Occupancy of waiting rooms varied substantially between rooms and over the clinic day. Light-touch estimation of occupancy density may help guide interventions to improve patient flow.

Identification of a stereotypic molecular arrangement of endogenous glycine receptors at spinal cord synapses.

Precise quantitative information about the molecular architecture of synapses is essential to understanding the functional specificity and downstream signaling processes at specific populations of synapses. Glycine receptors (GlyRs) are the primary fast inhibitory neurotransmitter receptors in the spinal cord and brainstem. These inhibitory glycinergic networks crucially regulate motor and sensory processes. Thus far, the nanoscale organization of GlyRs underlying the different network specificities has not been defined. Here, we have quantitatively characterized the molecular arrangement and ultra-structure of glycinergic synapses in spinal cord tissue using quantitative super-resolution correlative light and electron microscopy. We show that endogenous GlyRs exhibit equal receptor-scaffold occupancy and constant packing densities of about 2000 GlyRs µm-2 at synapses across the spinal cord and throughout adulthood, even though ventral horn synapses have twice the total copy numbers, larger postsynaptic domains, and more convoluted morphologies than dorsal horn synapses. We demonstrate that this stereotypic molecular arrangement is maintained at glycinergic synapses in the oscillator mouse model of the neuromotor disease hyperekplexia despite a decrease in synapse size, indicating that the molecular organization of GlyRs is preserved in this hypomorph. We thus conclude that the morphology and size of inhibitory postsynaptic specializations rather than differences in GlyR packing determine the postsynaptic strength of glycinergic neurotransmission in motor and sensory spinal cord networks.

An Orthogonal Covalent Connector System for the Efficient Assembly of Enzyme Cascades on DNA Nanostructures.

Combining structural DNA nanotechnology with the virtually unlimited variety of enzymes offers unique opportunities for generating novel biocatalytic devices. However, the immobilization of enzymes is still restricted by a lack of efficient covalent coupling techniques. The rational re-engineering of the genetically fusible SNAP-tag linker is reported here. By replacing five amino acids that alter the electrostatic properties of the SNAP_R5 variant, up to 11-fold increased coupling efficiency with benzylguanine-modified oligonucleotides and DNA origami nanostructures (DON) was achieved, resulting in typical occupancy densities of 75%. The novel SNAP_R5 linker can be combined with the equally efficient Halo-based oligonucleotide binding tag (HOB). Since both linkers exhibit neither cross-reactivity nor non-specific binding, they allowed orthogonal assembly of an enzyme cascade consisting of the stereoselective ketoreductase Gre2p and the cofactor-regenerating isocitrate dehydrogenase on DON. The cascade showed approximately 1.6-fold higher activity in a stereoselective cascade reaction than the corresponding free solubilized enzymes. The connector system presented here and the methods used to validate it represent important tools for further development of DON-based multienzyme systems to investigate mechanistic effects of substrate channeling and compartmentalization relevant for exploitation in biosensing and catalysis.

Developing a Data-driven school building stock energy and indoor environmental quality modelling method

The school building sector has a pivotal role to play in the transition to a low carbon UK economy. School buildings are responsible for 15% of the country’s public sector carbon emissions, with space heating currently making up the largest proportion of energy use and associated costs in schools. Children spend a large part of their waking life in school buildings. There is substantial evidence that poor indoor air quality and thermal discomfort can have detrimental impacts on the performance, wellbeing and health of schoolchildren and school staff. Maintaining high indoor environmental quality whilst reducing energy demand and carbon emissions in schools is challenging due to the unique operational characteristics of school environments, e.g. high and intermittent occupancy densities or changes in occupancy patterns throughout the year. Furthermore, existing data show that 81% of the school building stock in England was constructed before 1976. Challenges facing the ageing school building stock may be exacerbated in the context of ongoing and future climate change.In recent decades, building stock modelling has been widely used to quantify and evaluate the current and future energy and indoor environmental quality performance of large numbers of buildings at the neighbourhood, city, regional or national level. Building stock models commonly use building archetypes, which aim to represent the diversity of building stocks through frequently occurring building typologies.The aim of this paper is to introduce the Data dRiven Engine for Archetype Models of Schools (DREAMS), a novel, data-driven, archetype-based school building stock modelling framework. DREAMS enables the detailed representation of the school building stock in England through the statistical analysis of two large scale and highly detailed databases provided by the UK Government: (i) the Property Data Survey Programme (PDSP) from the Department for Education (DfE), and (ii) Display Energy Certificates (DEC). In this paper, the development of 168 building archetypes representing 9,551 primary schools in England is presented. The energy consumption of the English primary school building stock was modelled for a typical year under the current climate using the widely tested and applied building performance software EnergyPlus. For the purposes of modelling validation, the DREAMS space heating demand predictions were compared against average measured energy consumption of the schools that were represented by each archetype. It was demonstrated that the simulated fossil-thermal energy consumption of a typical primary school in England was only 7% higher than measured energy consumption (139 kWh/m2/y simulated, compared to 130 kWh/m2/y measured). The building stock model performs better at predicting the energy performance of naturally ventilated buildings, which constitute 97% of the stock, than that of mechanically ventilated ones. The framework has also shown capabilities in predicting energy consumption on a more localised scale. The London primary school building stock was examined as a case study.School building stock modelling frameworks such as DREAMS can be powerful tools that aid decision-makers to quantify and evaluate the impact of a wide range of building stock-level policies, energy efficiency interventions and climate change scenarios on school energy and indoor environmental performance.

A systematic approach to estimating the effectiveness of multi-scale IAQ strategies for reducing the risk of airborne infection of SARS-CoV-2

The unprecedented coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has made more than 125 million people infected and more than 2.7 million people dead globally. Airborne transmission has been recognized as one of the major transmission routes for SARS-CoV-2. This paper presents a systematic approach for evaluating the effectiveness of multi-scale IAQ control strategies in mitigating the infection risk in different scenarios. The IAQ control strategies across multiple scales from a whole building to rooms, and to cubical and personal microenvironments and breathing zone, are introduced, including elevated outdoor airflow rates, high-efficiency filters, advanced air distribution strategies, standalone air cleaning technologies, personal ventilation and face masks. The effectiveness of these strategies for reducing the risk of COVID-19 infection are evaluated for specific indoor spaces, including long-term care facility, school and college, meat plant, retail stores, hospital, office, correctional facility, hotel, restaurant, casino and transportation spaces like airplane, cruise ship, subway, bus and taxi, where airborne transmission are more likely to occur due to high occupancy densities. The baseline cases of these spaces are established according to the existing standards, guidelines or practices. Several integrated mitigation strategies are recommended and classified based on their relative cost and effort of implementation for each indoor space. They can be applied to help meet the current challenge of ongoing COVID-19, and provide better preparation for other possible epidemics and pandemics of airborne infectious diseases in the future.

Indoor air quality (IAQ) in naturally-ventilated primary schools in the UK: Occupant-related factors

Indoor Air Quality (IAQ) is affected by Context, Occupant and Building (COB) related factors. This paper evaluates IAQ as a function of occupant-related factors including occupants' Adaptive Behaviours (ABs), occupancy patterns, occupant's CO2 generation rates and occupancy density. This study observed occupant-related factors of 805 children in 29 naturally-ventilated (NV) classrooms in UK primary schools during Non-Heating and Heating seasons.Occupant-related factors affecting IAQ include occupants' adaptive behaviours, occupancy patterns, occupants' CO2 generation rate and occupancy densities. Results of this study suggest that a classroom with high potentials for natural ventilation does not necessarily provide adequate IAQ, however, occupants’ good practice of ABs is also required. Average occupancy densities to have CO2 levels of 1000 ± 50 ppm are suggested to be 2.3 ± 0.05m2/p and 7.6 ± 0.25 m3/p. These values correspond to the classroom area of 62.1 ± 1.35 m2 and volume of 205.2 ± 6.75 m3 with a height of 3.3 m. Mean CO2 level is maintained below 900 ppm when all occupant-related factors are in the favour of IAQ, however, it exceeds 1300 ppm when none of the occupant-related factors are in favour of IAQ.It is shown that 17% of CO2 variations are explained by open area (m2), 14% by occupants' generation rates (cm3/s) and 11% by occupancy density (m3/p). IAQ is mostly affected by occupants’ adaptive behaviours than other occupant-related factors in naturally-ventilated classrooms.

Implications of supplying district heat to a new urban residential area in Sweden

Here we analyze the cost, primary energy and CO2 implications of supplying district heat, considering different supply and return temperatures, to a new residential area in Växjö, Sweden. We explore four land exploitation alternatives consisting different types of buildings with various heated floor areas as well as occupancy densities and two levels of building energy efficiency, based on the Swedish building code and passive house criteria. The analysis shows that energy performance of the buildings and land exploitation alternatives strongly influence the annual heat demand and its profile, which steers the design of the local heat distribution network. Additionally, supply and return temperatures of district heat somewhat influence the design of the network. The distribution heat losses could be reduced by 25% and 50% if district heating systems of 65/30 °C and 50/20 °C, respectively, are used instead of a conventional 80/40 °C system. However, for the same land exploitation alternative, the local distribution heat losses are about the same whether or not the buildings are designed to meet the Swedish building code or passive house criteria, since the same pipe distance is required and the variation of pipe diameters is small. A 50/20 °C system increases electricity use to boost hot water temperature to avoid the risk of legionella bacteria, and this influences quantity of district heat supply, primary energy use and costs. Therefore, a 65/30 °C system appears to be more primary energy and cost efficient than a 50/20 °C system. Increased insulation of district heating network reduces heat losses but this is not cost effective due to increased investment cost. The results are similar whether or not the analysis is based on current energy supply or future renewable based energy supply. This study increases understanding of strategies for planning and designing new urban residential areas and their energy supply systems to reduce primary energy use as well as monetary costs, and to minimize the climate impacts of the built environment.

Multiplexing polysome profiling experiments to study translation in Escherichia coli.

Polysome profiling is a widely used method to monitor the translation status of mRNAs. Although it is theoretically a simple technique, it is labor intensive. Repetitive polysome fractionation rapidly generates a large number of samples to be handled in the downstream processes of protein elimination, RNA extraction and quantification. Here, we propose a multiplex polysome profiling experiment in which distinct cellular extracts are pooled before loading on the sucrose gradient for fractionation. We used the multiplexing method to study translation in E. coli. Multiplexing polysome profiling experiments provided similar mRNA translation status to that obtained with the non-multiplex method with comparable distribution of mRNA copies between the polysome profiling fractions, similar ribosome occupancy and ribosome density. The multiplexing method was used for parallel characterization of gene translational responses to changing mRNA levels. When the mRNA level of two native genes, cysZ and lacZ was increased by transcription induction, their global translational response was similar, with a higher ribosome load leading to increased ribosome occupancy and ribosome densities. However the pattern and the magnitude of the translational response were gene specific. By reducing the number of polysome profiling experiments, the multiplexing method saved time and effort and reduced cost and technical bias. This method would be useful to study the translational effect of mRNA sequence-dependent parameters that often require testing multiple samples and conditions in parallel.

Stream permanence is related to crayfish occupancy and abundance in the Ozark Highlands, USA

AbstractCrayfish use of intermittent streams is especially important to understand in the face of global climate change. We examined the influence of stream permanence and local habitat on crayfish occupancy and species densities in the Ozark Highlands, USA. We sampled in June and July 2014 and 2015. We used a quantitative kick–seine method to sample crayfish presence and abundance at 20 stream sites with 32 surveys/site in the Upper White River drainage, and we measured associated local environmental variables each year. We modeled site occupancy and detection probabilities with the software PRESENCE, and we used multiple linear regressions to identify relationships between crayfish species densities and environmental variables. Occupancy of all crayfish species was related to stream permanence. Faxonius meeki was found exclusively in intermittent streams, whereas Faxonius neglectus and Faxonius luteus had higher occupancy and detection probability in permanent than in intermittent streams, and Faxonius ...

CO2 concentration and occupancy density in the critical zones served by the VAV system

This article presents the results obtained from monitoring a VAV system with highly diversified zone occupancy density are presented in the article. The investigated VAV system meets the load for 72 zones (68 perimeters and 4 interiors) consisting of classrooms, offices, conference rooms, etc. with highly diversified occupancy densities from 1.875 to 2.5 m 2 /person for the classrooms and from 10 to 15 m 2 /person for the offices. The monitoring shows that the CO 2 concentration can exceed the set point in the critical rooms. Simulation results are also presented in the article to show that it is often impossible to adjust the operation of such VAV systems because the adjusted System Outdoor Air Fractions, % OA, can reach 100% even where the zone CO 2 concentration is not respected. The presented monitoring and simulation results were obtained in the winter, with the VAV system operating at partial load and with the minimum outdoor air flowrate required by the economizer system. As shown in the article, to respect the zone set point CO 2 concentration in such period, the VAV system must operate mostly at a %OA equal to 100% instead of its minimum value. To circumvent this, the supply zone air flow rate may have to be designed taking into account the CO 2 concentration resulting from the critical zones occupancy density.

Correlations between household occupancy and malaria vector biting risk in rural Tanzanian villages: implications for high-resolution spatial targeting of control interventions

BackgroundFine-scale targeting of interventions is increasingly important where epidemiological disease profiles depict high geographical stratifications. This study verified correlations between household biomass and mosquito house-entry using experimental hut studies, and then demonstrated how geographical foci of mosquito biting risk can be readily identified based on spatial distributions of household occupancies in villages.MethodsA controlled 4 × 4 Latin square experiment was conducted in rural Tanzania, in which no, one, three or six adult male volunteers slept under intact bed nets, in experimental huts. Mosquitoes entering the huts were caught using exit interception traps on eaves and windows. Separately, monthly mosquito collections were conducted in 96 randomly selected households in three villages using CDC light traps between March-2012 and November-2013. The number of people sleeping in the houses and other household and environmental characteristics were recorded. ArcGIS 10 (ESRI-USA) spatial analyst tool, Gi* Ord Statistic was used to analyse clustering of vector densities and household occupancy.ResultsThe densities of all mosquito genera increased in huts with one, three or six volunteers, relative to huts with no volunteers, and direct linear correlations within tested ranges (P < 0.001). Significant geographical clustering of indoor densities of malaria vectors, Anopheles arabiensis and Anopheles funestus, but not Culex or Mansonia species occurred in locations where households with highest occupancy were also most clustered (Gi* P ≤ 0.05, and Gi* Z-score ≥1.96).ConclusionsThis study demonstrates strong correlations between household occupancy and malaria vector densities in households, but also spatial correlations of these variables within and between villages in rural southeastern Tanzania. Fine-scale clustering of indoor densities of vectors within and between villages occurs in locations where houses with highest occupancy are also clustered. The study indicates potential for using household census data to preliminarily identify households with greatest Anopheles mosquito biting risk.