Metal oxide gas sensors are predominant solid-state gas detecting devices for domestic, commercial and industrial applications, which have many advantages such as low cost, easy production, and compact size. However, the performance of such sensors is significantly influenced by the morphology and structure of sensing materials, resulting in a great obstacle for gas sensors based on bulk materials or dense films to achieve highly-sensitive properties. Lots of metal oxide nanostructures have been developed to improve the gas sensing properties such as sensitivity, selectivity, response speed, and so on. Here, we provide a brief overview of metal oxide nanostructures and their gas sensing properties from the aspects of particle size, morphology and doping. When the particle size of metal oxide is close to or less than double thickness of the space-charge layer, the sensitivity of the sensor will increase remarkably, which would be called “small size effect”, yet small size of metal oxide nanoparticles will be compactly sintered together during the film coating process which is disadvantage for gas diffusion in them. In view of those reasons, nanostructures with many kinds of shapes such as porous nanotubes, porous nanospheres and so on have been investigated, that not only possessed large surface area and relatively mass reactive sites, but also formed relatively loose film structures which is an advantage for gas diffusion. Besides, doping is also an effective method to decrease particle size and improve gas sensing properties. Therefore, the gas sensing properties of metal oxide nanostructures assembled by nanoparticles are reviewed in this article. The effect of doping is also summarized and finally the perspectives of metal oxide gas sensor are given.
metal oxide; gas sensing; nanostructure; size effect; doping
This paper presents a review and analysis of the research that has been carried out on dynamic calibration for optical-fiber solids concentration probes. An introduction to the optical-fiber solids concentration probe was given. Different calibration methods of optical-fiber solids concentration probes reported in the literature were reviewed. In addition, a reflection-type optical-fiber solids concentration probe was uniquely calibrated at nearly full range of the solids concentration from 0 to packed bed concentration. The effects of particle properties (particle size, sphericity and color) on the calibration results were comprehensively investigated. The results show that the output voltage has a tendency to increase with the decreasing particle size, and the effect of particle color on calibration result is more predominant than that of sphericity.
optical-fiber probe; solids concentration; calibration method; gas-solid two-phase flows
In a health management system, prognostics, which is an engineering discipline that predicts a system's future health, is an important aspect yet there is currently limited research in this field. In this paper, a hybrid approach for prognostics is proposed. The approach combines the least squares support vector regression (LSSVR) with the hidden Markov model (HMM). Features extracted from sensor signals are used to train HMMs, which represent different health levels. A LSSVR algorithm is used to predict the feature trends. The LSSVR training and prediction algorithms are modified by adding new data and deleting old data and the probabilities of the predicted features for each HMM are calculated based on forward or backward algorithms. Based on these probabilities, one can determine a system's future health state and estimate the remaining useful life (RUL). To evaluate the proposed approach, a test was carried out using bearing vibration signals. Simulation results show that the LSSVR/HMM approach can forecast faults long before they occur and can predict the RUL. Therefore, the LSSVR/HMM approach is very promising in the field of prognostics.
prognostics; least squares support vector regression; hidden Markov model; remaining useful life
Bell-shaped vibratory angular rate gyro (abbreviated as BVG) is a new type Coriolis vibratory gyro that was inspired by Chinese traditional clocks. The resonator fuses based on a variable thickness axisymmetric multicurved surface shell. Its characteristics can directly influence the performance of BVG. The BVG structure not only has capabilities of bearing high overload, high impact and, compared with the tuning fork, vibrating beam, shell and a comb structure, but also a higher frequency to overcome the influence of the disturbance of the exterior environment than the same sized hemispherical resonator gyroscope (HRG) and the traditional cylinder vibratory gyroscope. It can be widely applied in high dynamic low precision angular rate measurement occasions. The main work is as follows: the issue mainly analyzes the structure and basic principle, and investigates the bell-shaped resonator's mathematical model. The reasonable structural parameters are obtained from finite element analysis and an intelligent platform. Using the current solid vibration gyro theory analyzes the structural characteristics and principles of BVG. The bell-shaped resonator is simplified as a paraboloid of the revolution mechanical model, which has a fixed closed end and a free opened end. It obtains the natural frequency and vibration modes based on the theory of elasticity. The structural parameters are obtained from the orthogonal method by the research on the structural parameters of the resonator analysis. It obtains the modal analysis, stress analysis and impact analysis with the chosen parameters. Finally, using the turntable experiment verifies the gyro effect of the BVG.
bell-shaped vibratory angular rate gyro; Coriolis vibratory gyro; bell-shaped resonator
Curb detection is an important research topic in environment perception, which is an essential part of unmanned ground vehicle (UGV) operations. In this paper, a new curb detection method using a 2D laser range finder in a semi-structured environment is presented. In the proposed method, firstly, a local Digital Elevation Map (DEM) is built using 2D sequential laser rangefinder data and vehicle state data in a dynamic environment and a probabilistic moving object deletion approach is proposed to cope with the effect of moving objects. Secondly, the curb candidate points are extracted based on the moving direction of the vehicle in the local DEM. Finally, the straight and curved curbs are detected by the Hough transform and the multi-model RANSAC algorithm, respectively. The proposed method can detect the curbs robustly in both static and typical dynamic environments. The proposed method has been verified in real vehicle experiments.
curb detection; laser range finder; mapping; dynamic environment
Electrical capacitance tomography (ECT) attempts to reconstruct the permittivity distribution of the cross-section of measurement objects from the capacitance measurement data, in which reconstruction algorithms play a crucial role in real applications. Based on the robust principal component analysis (RPCA) method, a dynamic reconstruction model that utilizes the multiple measurement vectors is presented in this paper, in which the evolution process of a dynamic object is considered as a sequence of images with different temporal sparse deviations from a common background. An objective functional that simultaneously considers the temporal constraint and the spatial constraint is proposed, where the images are reconstructed by a batching pattern. An iteration scheme that integrates the advantages of the alternating direction iteration optimization (ADIO) method and the forward-backward splitting (FBS) technique is developed for solving the proposed objective functional. Numerical simulations are implemented to validate the feasibility of the proposed algorithm.
electrical capacitance tomography; capacitance sensor; image reconstruction; inverse problem; robust principle component analysis; forward-backward splitting technique; alternating direction iteration optimization method
Over the last two decades, multiple classifier system (MCS) or classifier ensemble has shown great potential to improve the accuracy and reliability of remote sensing image classification. Although there are lots of literatures covering the MCS approaches, there is a lack of a comprehensive literature review which presents an overall architecture of the basic principles and trends behind the design of remote sensing classifier ensemble. Therefore, in order to give a reference point for MCS approaches, this paper attempts to explicitly review the remote sensing implementations of MCS and proposes some modified approaches. The effectiveness of existing and improved algorithms are analyzed and evaluated by multi-source remotely sensed images, including high spatial resolution image (QuickBird), hyperspectral image (OMISII) and multi-spectral image (Landsat ETM+). Experimental results demonstrate that MCS can effectively improve the accuracy and stability of remote sensing image classification, and diversity measures play an active role for the combination of multiple classifiers. Furthermore, this survey provides a roadmap to guide future research, algorithm enhancement and facilitate knowledge accumulation of MCS in remote sensing community.
multiple classifier system; classifier ensemble; remote sensing; classification
Sensing technology has been widely investigated and utilized for gas detection. Due to the different applicability and inherent limitations of different gas sensing technologies, researchers have been working on different scenarios with enhanced gas sensor calibration. This paper reviews the descriptions, evaluation, comparison and recent developments in existing gas sensing technologies. A classification of sensing technologies is given, based on the variation of electrical and other properties. Detailed introduction to sensing methods based on electrical variation is discussed through further classification according to sensing materials, including metal oxide semiconductors, polymers, carbon nanotubes, and moisture absorbing materials. Methods based on other kinds of variations such as optical, calorimetric, acoustic and gas-chromatographic, are presented in a general way. Several suggestions related to future development are also discussed. Furthermore, this paper focuses on sensitivity and selectivity for performance indicators to compare different sensing technologies, analyzes the factors that influence these two indicators, and lists several corresponding improved approaches.
gas sensing methods; sensing materials; sensitivity; selectivity
New design and optimization of charge pump rectifiers using diode-connected MOS transistors is presented in this paper. An analysis of the output voltage and Power Conversion Efficiency (PCE) is given to guide and evaluate the new design. A novel diode-connected MOS transistor for UHF rectifiers is presented and optimized, and a high efficiency N-stage charge pump rectifier based on this new diode-connected MOS transistor is designed and fabricated in a SMIC 0.18-μm 2P3M CMOS embedded EEPROM process. The new diode achieves 315 mV turn-on voltage and 415 nA reverse saturation leakage current. Compared with the traditional rectifier, the one based on the proposed diode-connected MOS has higher PCE, higher output voltage and smaller ripple coefficient. When the RF input is a 900-MHz sinusoid signal with the power ranging from −15 dBm to −4 dBm, PCEs of the charge pump rectifier with only 3-stage are more than 30%, and the maximum output voltage is 5.5 V, and its ripple coefficients are less than 1%. Therefore, the rectifier is especially suitableto passive UHF RFID tag IC and implantable devices.
radio frequency identification; passive transponders; diode-connected MOS transistor; rectifier; power conversion efficiency
A surface-acoustic-wave (SAW) gas sensor with a low detection limit and fast response for volatile organic compounds (VOCs) based on the condensate-adsorption effect detection is developed. In this sensor a gas chromatography (GC) column acts as the separator element and a dual-resonator oscillator acts as the detector element. Regarding the surface effective permittivity method, the response mechanism analysis, which relates the condensate-adsorption effect, is performed, leading to the sensor performance prediction prior to fabrication. New designs of SAW resonators, which act as feedback of the oscillator, are devised in order to decrease the insertion loss and to achieve single-mode control, resulting in superior frequency stability of the oscillator. Based on the new phase modulation approach, excellent short-term frequency stability (±3 Hz/s) is achieved with the SAW oscillator by using the 500 MHz dual-port resonator as feedback element. In a sensor experiment investigating formaldehyde detection, the implemented SAW gas sensor exhibits an excellent threshold detection limit as low as 0.38 pg.
gas sensor; gas chromatography (GC); surface acoustic wave (SAW); threshold detection limit
Conventional fluorescence scanners utilize multiple filters to distinguish different fluorescent labels, and problems arise because of this filter-based mechanism. In this work we propose a line-monitoring, hyperspectral fluorescence technique which is designed and optimized for applications in multi-channel microfluidic systems. In contrast to the filter-based mechanism, which only records fluorescent intensities, the hyperspectral technique records the full spectrum for every point on the sample plane. Multivariate data exploitation is then applied to spectra analysis to determine ratios of different fluorescent labels and eliminate unwanted artifacts. This sensor is designed to monitor multiple fluidic channels simultaneously, providing the potential for multi-analyte biosensing. The detection sensitivity is approximately 0.81 fluors/μm2, and this sensor is proved to act with a good homogeneity. Finally, a model experiment of detecting short oligonucleotides has demonstrated the biomedical application of this hyperspectral fluorescence biosensor.
hyperspectral fluorescence detection; microfluidic system; biosensor
We here report a rapid, sensitive, selective and label-free fluorescence detection method for cysteine (Cys). The conformation of mercury-specific DNA (MSD) changes from a random coil form to a hairpin structure in the presence of Hg2+ due to the formation of a thymine-Hg2+-thymine (T-Hg2+-T) complex. Cys can selectively coordinate with Hg2+ and extract it from the thymine-Hg2+-thymine complex. The hairpin structure dehybridizes and the fluorescence intensity of Sybr Green I (SG) decreases upon addition of Cys because SG efficiently discriminates mercury-specific DNA and mercury-specific DNA/Hg2+ complex. The detection can be finished within 5 min with high sensitivity and selectivity. In addition, we can obtain variable dynamic ranges for Cys by changing the concentration of MSD/Hg2+.
cysteine; competition assay; mercury-specific DNA; Hg2+; Sybr Green I
A new micro gyroscope based on the surface acoustic wave (SAW) gyroscopic effect was developed. The SAW gyroscopic effect is investigated by applying the surface effective permittivity method in the regime of small ratios of the rotation velocity and the frequency of the SAW. The theoretical analysis indicates that the larger velocity shift was observed from the rotated X-112°Y LiTaO3 substrate. Then, two SAW delay lines with reverse direction and an operation frequency of 160 MHz are fabricated on a same X-112°Y LiTaO3 chip as the feedback of two SAW oscillators, which act as the sensor element. The single-phase unidirectional transducer (SPUDT) and combed transducers were used to structure the delay lines to improve the frequency stability of the oscillator. The rotation of a piezoelectric medium gives rise to a shift of the propagation velocity of SAW due to the Coriolis force, resulting in the frequency shift of the SAW device, and hence, the evaluation of the sensor performance. Meanwhile, the differential structure was performed to double the sensitivity and compensate for the temperature effects. Using a precise rate table, the performance of the fabricated SAW gyroscope was evaluated experimentally. A sensitivity of 1.332 Hz deg−1 s at angular rates of up to 1,000 deg s−1 and good linearity are observed.
Coriolis force; gyroscopic effect; SAW gyroscope; surface effective permittivity
In this paper we propose a novel scheme able to automatically detect the intima and adventitia of both near and far walls of the common carotid artery in dynamic B-mode RF (radiofrequency) image sequences, with and without plaques. Via this automated system the lumen diameter changes along the heart cycle can be detected. Three image sequences have been tested and all results are compared to manual tracings made by two professional experts. The average errors for near and far wall detection are 0.058 mm and 0.067 mm, respectively. This system is able to analyze arterial plaques dynamically which is impossible to do manually due to the tremendous human workload involved.
intima; media; adventitia; CCA; plaque
In a randomly deployed and large scale wireless sensor network, coverage-redundant nodes consume much unnecessary energy. As a result, turning off these redundant nodes can prolong the network lifetime, while maintaining the degree of sensing coverage with a limited number of on-duty nodes. None of the off-duty eligibility rules in the literature, however, are sufficient and necessary conditions for eligible nodes. Hence redundancy or blind points might be incurred. In this paper we propose a complete Eligibility Rule based on Perimeter Coverage (ERPC) for a node to determine its eligibility for sleeping. ERPC has a computational complexity of O(N2log(N)), lower than the eligibility rule in the Coverage Control Protocol (CCP), O(N3), where N is the number of neighboring nodes. We then present a Coverage Preserving Protocol (CPP) to schedule the work state of eligible nodes. The main advantage of CPP over the Ottawa protocol lies in its ability to configure the network to any specific coverage degree, while the Ottawa protocol does not support different coverage configuration. Moreover, as a localized protocol, CPP has better adaptability to dynamic topologies than centralized protocols. Simulation results indicate that CPP can preserve network coverage with fewer active nodes than the Ottawa protocol. In addition, CPP is capable of identifying all the eligible nodes exactly while the CCP protocol might result in blind points due to error decisions. Quantitative analysis and experiments demonstrate that CPP can extend the network lifetime significantly while maintaining a given coverage degree.
Wireless Sensor Networks; Coverage Control Protocol; Perimeter Coverage; Off-duty Eligibility Rule
Detection of DNA sequences has received broad attention due to its potential applications in a variety of fields. As sensitivity of DNA biosensors is determined by signal variation of hybridization events, the signal enhancement is of great significance for improving the sensitivity in DNA detection, which still remains a great challenge. Nanomaterials, which possess some unique chemical and physical properties caused by nanoscale effects, provide a new opportunity for developing novel nanomaterial-based signal-enhancers for DNA biosensors. In this review, recent progress concerning this field, including some newly-developed signal enhancement approaches using quantum-dots, carbon nanotubes and their composites reported by our group and other researchers are comprehensively summarized. Reports on signal enhancement of DNA biosensors by non-nanomaterials, such as enzymes and polymer reagents, are also reviewed for comparison. Furthermore, the prospects for developing DNA biosensors using nanomaterials as signal-enhancers in future are also indicated.
DNA detection; sensitivity; nanosemiconductors; quantum-dots; nanopaticles; carbon nanotubes
The basic operation of a Delay Tolerant Sensor Network (DTSN) is to finish pervasive data gathering in networks with intermittent connectivity, while the publish/subscribe (Pub/Sub for short) paradigm is used to deliver events from a source to interested clients in an asynchronous way. Recently, extension of Pub/Sub systems in DTSNs has become a promising research topic. However, due to the unique frequent partitioning characteristic of DTSNs, extension of a Pub/Sub system in a DTSN is a considerably difficult and challenging problem, and there are no good solutions to this problem in published works. To ad apt Pub/Sub systems to DTSNs, we propose CED, a community-based event delivery protocol. In our design, event delivery is based on several unchanged communities, which are formed by sensor nodes in the network according to their connectivity. CED consists of two components: event delivery and queue management. In event delivery, events in a community are delivered to mobile subscribers once a subscriber comes into the community, for improving the data delivery ratio. The queue management employs both the event successful delivery time and the event survival time to decide whether an event should be delivered or dropped for minimizing the transmission overhead. The effectiveness of CED is demonstrated through comprehensive simulation studies.
event delivery; publish/subscribe; queue management; community
The total atmospheric water vapor content (TAWV) and land surface temperature (LST) play important roles in meteorology, hydrology, ecology and some other disciplines. In this paper, the ENVISAT/AATSR (The Advanced Along-Track Scanning Radiometer) thermal data are used to estimate the TAWV and LST over the Loess Plateau in China by using a practical split window algorithm. The distribution of the TAWV is accord with that of the MODIS TAWV products, which indicates that the estimation of the total atmospheric water vapor content is reliable. Validations of the LST by comparing with the ground measurements indicate that the maximum absolute derivation, the maximum relative error and the average relative error is 4.0K, 11.8% and 5.0% respectively, which shows that the retrievals are believable; this algorithm can provide a new way to estimate the LST from AATSR data.
Land surface temperature; Total atmospheric water vapor content; AATSR; Retrieval; MODIS; the Loess Plateau
Driving safety has become a global topic of discussion with the recent development of the Smart Car concept. Many of the current car safety monitoring systems are based on image discrimination techniques, such as sensing the vehicle drifting from the main road, or changes in the driver's facial expressions. However, these techniques are either too simplistic or have a low success rate as image processing is easily affected by external factors, such as weather and illumination. We developed a drowsiness detection mechanism based on an electroencephalogram (EEG) reading collected from the driver with an off-the-shelf mobile sensor. This sensor employs wireless transmission technology and is suitable for wear by the driver of a vehicle. The following classification techniques were incorporated: Artificial Neural Networks, Support Vector Machine, and k Nearest Neighbor. These classifiers were integrated with integration functions after a genetic algorithm was first used to adjust the weighting for each classifier in the integration function. In addition, since past studies have shown effects of music on a person's state-of-mind, we propose a personalized music recommendation mechanism as a part of our system. Through the in-car stereo system, this music recommendation mechanism can help prevent a driver from becoming drowsy due to monotonous road conditions. Experimental results demonstrate the effectiveness of our proposed drowsiness detection method to determine a driver's state of mind, and the music recommendation system is therefore able to reduce drowsiness.
classifier; drowsy detection; EEG sensor; electroencephalogram; refreshing music
Strapdown inertial navigation systems (INS) need an alignment process to determine the initial attitude matrix between the body frame and the navigation frame. The conventional alignment process is to compute the initial attitude matrix using the gravity and Earth rotational rate measurements. However, under mooring conditions, the inertial measurement unit (IMU) employed in a ship's strapdown INS often suffers from both the intrinsic sensor noise components and the external disturbance components caused by the motions of the sea waves and wind waves, so a rapid and precise alignment of a ship's strapdown INS without any auxiliary information is hard to achieve. A robust solution is given in this paper to solve this problem. The inertial frame based alignment method is utilized to adapt the mooring condition, most of the periodical low-frequency external disturbance components could be removed by the mathematical integration and averaging characteristic of this method. A novel prefilter named hidden Markov model based Kalman filter (HMM-KF) is proposed to remove the relatively high-frequency error components. Different from the digital filters, the HMM-KF barely cause time-delay problem. The turntable, mooring and sea experiments favorably validate the rapidness and accuracy of the proposed self-alignment method and the good de-noising performance of HMM-KF.
inertial navigation systems (INS); alignment; mooring condition; inertial measurement unit (IMU); inertial frame; hidden Markov model; Kalman filter
A monoclonal antibody specifically recognizing dibutyl phthalate (DBP) was prepared based on a hapten (di-n-butyl-4-aminophthalate). After optimizing various parameters such as concentrations of antibody, coating antigen and composition of the assay buffer, an inhibition curve was plotted with the 50% inhibition concentration value (IC50) 33.6 ± 2.5 ng/mL. A low level of cross-reactivity (<5%) was found for other phthalate esters. Recovery tests were conducted using liquor simulant (a mixture of water and ethanol) at two fortification levels (100 ng/mL and 300 ng/mL). The recovery rates ranged from 84.7% to 94.5% with a coefficient of variation between 7.1% and 12.8%. Nine liquor samples of different alcoholic strengths were detected using the proposed measure and confirmatory analysis was performed using liquid chromatography-mass spectroscopy (LC-MS). The detection results showed good consistency between the two measures and all the data above indicated that the proposed ELISA could be applied in DBP screening.
di-n-butyl phthalate; ELISA; liquor; monoclonal antibody
Doping with other elements is one of the efficient ways to modify the physical and chemical properties of TiO2 nanomaterials. In the present work, Ni-doped TiO2 nanotubes were fabricated through anodic oxidation of NiTi alloy and further annealing treatment. The hydrogen sensing properties of the nanotube sensor were investigated. It was found that the Ni-doped TiO2 nanotubes were sensitive to an atmosphere of 1,000 ppm hydrogen, showing a good response at both room temperature and elevated temperatures. A First-Principle simulation revealed that, in comparison with pure anatase TiO2 oxide, Ni doping in the TiO2 oxide could result in a decreased bandgap. When the oxide sensor adsorbed a certain amount of hydrogen the bandgap increased and the acceptor impurity levels was generated, which resulted in a change of the sensor resistance.
TiO2; nanotubes; doping; hydrogen sensor
Data from multiple sensors are frequently used in Earth science to gain a more complete understanding of spatial information changes. Higher quality and mutual consistency are prerequisites when multiple sensors are jointly used. The HJ-1A/B satellites successfully launched on 6 September 2008. There are four charge-coupled device (CCD) sensors with uniform spatial resolutions and spectral range onboard the HJ-A/B satellites. Whether these data are keeping consistency is a major issue before they are used. This research aims to evaluate the data consistency and radioactive quality from the four CCDs. First, images of urban, desert, lake and ocean are chosen as the objects of evaluation. Second, objective evaluation variables, such as mean, variance and angular second moment, are used to identify image performance. Finally, a cross validation method are used to ensure the correlation of the data from the four HJ-1A/B CCDs and that which is gathered from the moderate resolution imaging spectro-radiometer (MODIS). The results show that the image quality of HJ-1A/B CCDs is stable, and the digital number distribution of CCD data is relatively low. In cross validation with MODIS, the root mean square errors of bands 1, 2 and 3 range from 0.055 to 0.065, and for band 4 it is 0.101. The data from HJ-1A/B CCD have better consistency.
sensor; radioactive quality evaluation; cross validation; HJ-1A/B CCD
Timely and accurate condition monitoring and fault diagnosis of rotating machinery are very important to maintain a high degree of availability, reliability and operational safety. This paper presents a novel intelligent method based on local mean decomposition (LMD) and multi-class reproducing wavelet support vector machines (RWSVM), which is applied to diagnose rotating machinery faults. First, the sensor-based vibration signals measured from the rotating machinery are preprocessed by the LMD method and product functions (PFs) are produced. Second, statistic features are extracted to acquire more fault characteristic information from the sensitive PF. Finally, these features are fed into a multi-class RWSVM to identify the rotating machinery health conditions. The experimental results validate the effectiveness of the proposed RWSVM method in identifying rotating machinery fault patterns accurately and effectively and its superiority over that based on the general SVM.
local mean decomposition; reproducing wavelet kernel support vector machines; fault diagnosis; sensor-based vibration signals; rotating machinery
The remote detection of the concentration of methane at room temperature is performed by a sensor that is configured by the combination of radio frequency identification (RFID), and functionalized carbon nanotubes (CNTs). The proposed sensor is schemed as a thin film RFID tag in a polyethylene substrate, on which a metal trace dipole, a metal trace T impedance matching networks, a 0.5 μm-CMOS RF/DC rectifier chipset and a sensor head of palladium-decorated single walled carbon nanotubes (Pd-SWCNTs) are surface mounted in cascade. The performances of the sensor are examined and described by the defined parameters of the received signal strength index (RSSI) and the comparative analog identifier (ΔAID). Results validate the sensor's ability to detect molecules of methane at room temperature, showing that the RSSI can increase 4 dB and the ΔAID can increase 3% in response to methane concentrations ranging from zero to 100 ppm.
gas sensor; methane concentration; Pd-SWCNTs; RFID; room temperature