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1.
Braz. j. biol ; 84: e259259, 2024. tab, graf
Artigo em Inglês | LILACS, VETINDEX | ID: biblio-1364517

RESUMO

Rice is a widely consumed staple food for a large part of the world's human population. Approximately 90% of the world's rice is grown in Asian continent and constitutes a staple food for 2.7 billion people worldwide. Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae is one of the devastating diseases of rice. A field experiment was conducted during the year 2016 and 2017 to investigate the influence of different meteorological parameters on BLB development as well as the computation of a predictive model to forecast the disease well ahead of its appearance in the field. The seasonal dataset of disease incidence and environmental factors was used to assess five rice varieties/ cultivars (Basmati-2000, KSK-434, KSK-133, Super Basmati, and IRRI-9). The accumulated effect of two year environmental data; maximum and minimum temperature, relative humidity, wind speed, and rainfall, was studied and correlated with disease incidence. Average temperature (maximum & minimum) showed a negative significant correlation with BLB disease and all other variables; relative humidity, rainfall, and wind speed had a positive correlation with BLB disease development on individual varieties. Stepwise regression analysis was performed to indicate potentially useful predictor variables and to rule out incompetent parameters. Environmental data from the growing seasons of July to October 2016 and 2017 revealed that, with the exception of the lowest temperature, all environmental factors contributed to disease development throughout the cropping season. A disease prediction multiple regression model was developed based on two-year data (Y = 214.3-3.691 Max T-0.508 Min T + 0.767 RH + 2.521 RF + 5.740 WS), which explained 95% variability. This disease prediction model will not only help farmers in early detection and timely management of bacterial leaf blight disease of rice but may also help reduce input costs and improve product quality and quantity. The model will be both farmer and environmentally friendly.


O arroz é um alimento básico amplamente consumido por grande parte da população humana mundial. Aproximadamente 90% do arroz do mundo é cultivado no continente asiático e constitui um alimento básico para 2,7 bilhões de pessoas em todo o mundo. O crestamento bacteriano das folhas (BLB) causado por Xanthomonas oryzae pv. oryzae é uma das doenças devastadoras do arroz. Um experimento de campo foi realizado durante os anos de 2016 e 2017 para investigar a influência de diferentes parâmetros meteorológicos no desenvolvimento do BLB, bem como o cálculo de um modelo preditivo para prever a doença bem antes de seu aparecimento em campo. O conjunto de dados sazonais de incidência de doenças e fatores ambientais foi usado para avaliar cinco variedades/cultivares de arroz (Basmati-2000, KSK-434, KSK-133, Super Basmati e IRRI-9). O efeito acumulado de dados ambientais de dois anos; temperatura máxima e mínima, umidade relativa do ar, velocidade do vento e precipitação pluviométrica foram estudados e correlacionados com a incidência da doença. A temperatura média (máxima e mínima) apresentou correlação significativa negativa com a doença BLB e todas as outras variáveis; umidade relativa, precipitação e velocidade do vento tiveram uma correlação positiva com o desenvolvimento da doença BLB em variedades individuais. A análise de regressão stepwise foi realizada para indicar variáveis preditoras potencialmente úteis e para descartar parâmetros incompetentes. Os dados ambientais das safras de julho a outubro de 2016 e 2017 revelaram que, com exceção da temperatura mais baixa, todos os fatores ambientais contribuíram para o desenvolvimento da doença ao longo da safra. Um modelo de regressão múltipla de previsão de doença foi desenvolvido com base em dados de dois anos (Y = 214,3-3,691 Max T-0,508 Min T + 0,767 RH + 2,521 RF + 5,740 WS), que explicou 95% de variabilidade. Este modelo de previsão de doenças não só ajudará os agricultores na detecção precoce e gestão atempada da doença bacteriana das folhas do arroz, mas também pode ajudar a reduzir os custos de insumos e melhorar a qualidade e a quantidade do produto. O modelo será agricultor e ambientalmente amigável.


Assuntos
Oryza , Temperatura , Pragas da Agricultura , Umidade
2.
Food Microbiol ; 109: 104118, 2023 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-36309430

RESUMO

A longitudinal study was conducted in five conventional broiler farms during a 2-year period to determine the dynamics of Campylobacter infection in a warm climate region (north-eastern Spain). Weekly sampling of 63 flocks was performed upon one-day-old chick placement, including animal and environmental samples. Campylobacter spp. detection was assessed by culture and non-culture methods. Environmental samples were also obtained from cleaned and disinfected houses prior to chick placement. Thirty-nine flocks (61.90%) became colonized during the growing period. First bird excreting Campylobacter was detected in 10-day-old chicks and the earliest a whole flock became positive was at 14 days of age, while the latest was at 39 days. Once Campylobacter was detected in chickens, the whole flock was colonized within 2-13 days. Campylobacter farm prevalence (positive flocks) ranged from 53.85% to 83.33% in four out of five farms, while the remaining farm showed a lower prevalence (38.5%). Logistic regression model showed that Campylobacter infection was more likely under higher minimal indoor temperature as well as at higher minimal outdoor relative humidity, characteristic of warm climates such as those from Mediterranean countries. Ventilation type was also significant (P = 0.021). No clear farm effect or seasonality were observed. Biosecurity improvements, specially at house level, are needed in broiler farms to prevent flock colonization and reduce the current high flock prevalence.


Assuntos
Infecções por Campylobacter , Campylobacter , Doenças das Aves Domésticas , Animais , Galinhas , Infecções por Campylobacter/epidemiologia , Infecções por Campylobacter/veterinária , Fazendas , Doenças das Aves Domésticas/epidemiologia , Estudos Longitudinais , Temperatura , Umidade , Criação de Animais Domésticos/métodos , Prevalência
3.
Environ Monit Assess ; 195(1): 69, 2022 Nov 04.
Artigo em Inglês | MEDLINE | ID: mdl-36331671

RESUMO

Tropical forests sequester six times higher carbon than that released by humans annually into the atmosphere. These biodiversity-rich tropical forests have high net primary productivity (NPP), which differs among constituent plant communities. Tropical moist deciduous forests occupy 179,335 km2 of India's geographical area and constitute 44% of the country's total protected area (PA) forests. The productivity of these forests has neither been estimated specifically nor precisely. We measured the annual NPP of three predominant distinct community types, viz., mixed (DM), sal (SM), and teak (TP), in a tropical moist deciduous forest in northern India. The NPP was estimated from tree biomass data collected from nine long-term ecological research (LTER) plots of 1 ha each representing the above three community types. The estimated annual NPP were 10.28, 6.25, and 9.79 Mg ha-1 year-1 in DM; 8.93, 7.09, and 10.59 Mg ha-1 year-1 in SM; and 14.57, 7.14, and 13.56 Mg ha-1 year-1 in TP for the years 2010, 2011, and 2012, respectively. The NPP was correlated with tree density, height and DBH, species richness, diversity, microclimatic and edaphic variables, and leaf area index (LAI) using principal component analysis (PCA) and generalized linear modeling (GLM). Air temperature and humidity were strongly related to NPP in all the community types, while "complementarity" and "selection effects" contributed to the NPP in both the sal and mixed forest communities with equal importance, and the NPP in teak plantation ould point to "dominance effect."


Assuntos
Monitoramento Ambiental , Clima Tropical , Humanos , Temperatura , Umidade , Florestas , Árvores , Biomassa
4.
Sensors (Basel) ; 22(21)2022 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-36366109

RESUMO

In recent years, fire detection technologies have helped safeguard lives and property from hazards. Early fire warning methods, such as smoke or gas sensors, are ineffectual. Many fires have caused deaths and property damage. IoT is a fast-growing technology. It contains equipment, buildings, electrical systems, vehicles, and everyday things with computing and sensing capabilities. These objects can be managed and monitored remotely as they are connected to the Internet. In the Internet of Things concept, low-power devices like sensors and controllers are linked together using the concept of Low Power Wide Area Network (LPWAN). Long Range Wide Area Network (LoRaWAN) is an LPWAN product used on the Internet of Things (IoT). It is well suited for networks of things connected to the Internet, where terminals send a minute amount of sensor data over large distances, providing the end terminals with battery lifetimes of years. In this article, we design and implement a LoRaWAN-based system for smart building fire detection and prevention, not reliant upon Wireless Fidelity (Wi-Fi) connection. A LoRa node with a combination of sensors can detect smoke, gas, Liquefied Petroleum Gas (LPG), propane, methane, hydrogen, alcohol, temperature, and humidity. We developed the system in a real-world environment utilizing Wi-Fi Lora 32 boards. The performance is evaluated considering the response time and overall network delay. The tests are carried out in different lengths (0-600 m) and heights above the ground (0-2 m) in an open environment and indoor (1st Floor-3rd floor) environment. We observed that the proposed system outperformed in sensing and data transfer from sensing nodes to the controller boards.


Assuntos
Fontes de Energia Elétrica , Fumaça , Monitorização Fisiológica/métodos , Umidade , Temperatura
5.
Malar J ; 21(1): 325, 2022 Nov 11.
Artigo em Inglês | MEDLINE | ID: mdl-36369086

RESUMO

BACKGROUND: Seasonal patterns of malaria cases in many parts of Africa are generally associated with rainfall, yet in the dry seasons, malaria transmission declines but does not always cease. It is important to understand what conditions support these periodic cases. Aerial moisture is thought to be important for mosquito survival and ability to forage, but its role during the dry seasons has not been well studied. During the dry season aerial moisture is minimal, but intermittent periods may arise from the transpiration of peri-domestic trees or from some other sources in the environment. These periods may provide conditions to sustain pockets of mosquitoes that become active and forage, thereby transmitting malaria. In this work, humidity along with other ecological variables that may impact malaria transmission have been examined. METHODS: Negative binomial regression models were used to explore the association between peri-domestic tree humidity and local malaria incidence. This was done using sensitive temperature and humidity loggers in the rural Southern Province of Zambia over three consecutive years. Additional variables including rainfall, temperature and elevation were also explored. RESULTS: A negative binomial model with no lag was found to best fit the malaria cases for the full year in the evaluated sites of the Southern Province of Zambia. Local tree and granary night-time humidity and temperature were found to be associated with local health centre-reported incidence of malaria, while rainfall and elevation did not significantly contribute to this model. A no lag and one week lag model for the dry season alone also showed a significant effect of humidity, but not temperature, elevation, or rainfall. CONCLUSION: The study has shown that throughout the dry season, periodic conditions of sustained humidity occur that may permit foraging by resting mosquitoes, and these periods are associated with increased incidence of malaria cases. These results shed a light on conditions that impact the survival of the common malaria vector species, Anopheles arabiensis, in arid seasons and suggests how they emerge to forage when conditions permit.


Assuntos
Anopheles , Malária , Animais , Humanos , Malária/epidemiologia , Umidade , Estações do Ano , Mosquitos Vetores , Zâmbia/epidemiologia
6.
J R Soc Interface ; 19(196): 20210865, 2022 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-36382379

RESUMO

Globally, the spread and severity of COVID-19 have been distinctly non-uniform. Seasonality was suggested as a contributor to regional variability, but the relationship between weather and COVID-19 remains unclear and the focus of attention has been on outdoor conditions. Because humans spend most of their time indoors and because most transmission occurs indoors, we here, instead, investigate the hypothesis that indoor climate-particularly indoor relative humidity (RH)-may be the more relevant modulator of outbreaks. To study this association, we combined population-based COVID-19 statistics and meteorological measurements from 121 countries. We rigorously processed epidemiological data to reduce bias, then developed and experimentally validated a computational workflow to estimate indoor conditions based on outdoor weather data and standard indoor comfort conditions. Our comprehensive analysis shows robust and systematic relationships between regional outbreaks and indoor RH. In particular, we found intermediate RH (40-60%) to be robustly associated with better COVID-19 outbreak outcomes (versus RH < 40% or >60%). Together, these results suggest that indoor conditions, particularly indoor RH, modulate the spread and severity of COVID-19 outbreaks.


Assuntos
COVID-19 , Humanos , COVID-19/epidemiologia , Umidade , Tempo (Meteorologia) , Temperatura
7.
Sci Rep ; 12(1): 19722, 2022 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-36385128

RESUMO

Climatic conditions play a key role in the transmission and pathophysiology of respiratory tract infections, either directly or indirectly. However, their impact on the COVID-19 pandemic propagation is yet to be studied. This study aimed to evaluate the effects of climatic factors such as temperature, rainfall, relative humidity, sunshine duration, and wind speed on the number of daily COVID-19 cases in Addis Ababa, Ethiopia. Data on confirmed COVID-19 cases were obtained from the National Data Management Center at the Ethiopian Public Health Institute for the period 10th March 2020 to 31st October 2021. Data for climatic factors were obtained from the Ethiopia National Meteorology Agency. The correlation between daily confirmed COVID-19 cases and climatic factors was measured using the Spearman rank correlation test. The log-link negative binomial regression model was used to fit the effect of climatic factors on COVID-19 transmission, from lag 0 to lag 14 days. During the study period, a total of 245,101 COVID-19 cases were recorded in Addis Ababa, with a median of 337 new cases per day and a maximum of 1903 instances per day. A significant correlation between COVID-19 cases and humidity was observed with a 1% increase in relative humidity associated with a 1.1% [IRRs (95%CI) 0.989, 95% (0.97-0.99)] and 1.2% [IRRs (95%CI) 0.988, (0.97-0.99)] decrease in COVID-19 cases for 4 and 5 lag days prior to detection, respectively. The highest increase in the effect of wind speed and rainfall on COVID-19 was observed at 14 lag days prior to detection with IRRs of 1.85 (95%CI 1.26-2.74) and 1.078 (95%CI 1.04-1.12), respectively. The lowest IRR was 1.109 (95%CI 0.93-1.31) and 1.007 (95%CI 0.99-1.02) both in lag 0, respectively. The findings revealed that none of the climatic variables influenced the number of COVID-19 cases on the day of case detection (lag 0), and that daily average temperature and sunshine duration were not significantly linked with COVID-19 risk across the full lag period (p > 0.05). Climatic factors such as humidity, rainfall, and wind speed influence the transmission of COVID-19 in Addis Ababa, Ethiopia. COVID-19 cases have shown seasonal variations with the highest number of cases reported during the rainy season and the lowest number of cases reported during the dry season. These findings suggest the need to design strategies for the prevention and control of COVID-19 before the rainy seasons.


Assuntos
COVID-19 , Humanos , COVID-19/epidemiologia , Etiópia/epidemiologia , Pandemias , Incidência , Umidade
8.
J Mater Chem B ; 10(44): 9179-9187, 2022 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-36341761

RESUMO

Steady adhesion under varying humidity conditions is fundamentally challenging due to the barrier of interfacial water molecules. Here, we demonstrate a humidity-resistant gecko-inspired microfibrillar adhesive fabricated by using a specific phenyl-rich polysiloxane. In contrast with the great decline of macroadhesion with increasing humidity for the typical polydimethylsiloxane (PDMS) microfibrillar adhesives, strong macroadhesion of a microfibrillar adhesive fabricated using synthetic phenyl-rich polysiloxane maintains adhesion well across a wide relative humidity range (1% to 95%). Moreover, the pull-off strength is increased by 500% compared to that of phenyl-absent PDMS microfibrillar adhesives at extremely high humidity. Mechanism analysis demonstrates that the synergistic interplay of strong interfacial hydrophobicity leading to dry contact and bulk energy dissipation through massive aromatic π-π interactions contributes greatly to the reliable and strong humidity macroadhesion. The present results provide a better understanding of humidity macroadhesion as well as application potential for microfibrillar adhesives, which are proven to be reliable skin adhesive patches for long-term health-care that have to be exposed to varying humidity conditions of the skin surface.


Assuntos
Adesivos , Lagartos , Animais , Elastômeros , Umidade , Siloxanas
9.
J Adv Res ; 41: 49-62, 2022 11.
Artigo em Inglês | MEDLINE | ID: mdl-36328753

RESUMO

INTRODUCTION: Infra-red (IR) and visible light (VL) based systems developed for transmission of information about physical quantities (e.g. humidity, temperature) out from closed areas, cannot be effectively employed in case of specific conditions in a targeted environment (because of fog or vapor for example). OBJECTIVES: In this work, we introduce a concept of wireless short-range transmitter and receiver to sense physical quantities, for instance temperature, with slow variation. The proposed concept is able to transmit analog-based information from isolated environments (e.g. aquariums or environments for plant growing) with high immunity against vapor and fog that limits standard optical (laser, IR band) methods of communication. METHODS: In this work, a new concept of short range radiofrequency (RF) communication device consisting of transmitting and receiving parts build from active devices fabricated in 0.35 µm I3T25 3.3 VCMOS process and ferrite antennas is selected. RF part uses medium-wave propagation within 10 mm distance at frequency 700 kHz. Such an approach offers minimal path loss of the radiated energy of a signal and low-gain amplification required for restoration of similar levels as available at the transmitting side. RESULTS: The processing of base-band signals of simple (sine wave) and complex (electrocardiogram) character was verified experimentally through the system. Application example of temperature monitoring in a closed environment, based on a temperature sensor (thermistor), verifies operationability in temperature range from 10 °C up to 50 °C. CONCLUSION: Compared to state-of-the-art solution, the presented concept has several advantages, for instance: less complexity; using of simpler type of modulation and demodulation; lower power consumption and significantly reduced issues caused by an environment with special transmission conditions (e.g. fog and vapor). The obtained results are in good agreement with expectations. Among others, the presented system brings beneficial performances for similar applications targeting on monitoring of low-frequency or slowly varying signals.


Assuntos
Eletrocardiografia , Ondas de Rádio , Temperatura , Desenho de Equipamento , Umidade
10.
Animal ; 16(11): 100662, 2022 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-36327798

RESUMO

The search for criteria that allow the quantification of the level of thermotolerance of an animal is a major challenge in animal production. Different criteria have been proposed to date, mainly the use of routine milk recording and weather information or the collection of physiological measures related with heat stress. This study aimed at quantifying the association between indicators of heat tolerance derived from productive and physiological traits. For this purpose, two physiological traits, rectal temperature (RT) and respiratory rate (RR), and nine productive traits (milk yield, fat, protein and lactose yields and contents, casein and urea contents) were measured from June to September of 2018 in three flocks of Manchega sheep. A total of 462 lactating ewes participated in the study. Air temperature (Ta), relative humidity (RH) and associated temperature and humidity index (THI) were recorded inside the barn and also obtained from the closest weather station from the national meteorological network, and used to produce several measurements of heat load on animals. Based on the results of fits for quadratic and cubic regressions on the alternative heat load measures, the cubic regression on Ta and THI obtained inside the barn at time of recording yielded the best fit for physiological and productive parameters. The use of weather information taken from the official weather station closest to the farm also produced similar estimates and could be considered as a good alternative when on-farm meteorological data are not available. Two-trait random regression models that involved individual intercept and slope of response to heat load were used to obtain correlations between basal levels and heat tolerance within and across traits. Estimated correlations showed that animals with smaller vs larger basal levels of RT and RR tend to be more vs less heat tolerant (correlations up to 0.46) and that slopes of increase for RR and RT under heat stress were highly correlated (0.82). Estimated correlations between tolerance criteria from production vs physiology were up to -0.5 (between milk yield and RT), indicating that animals that show less increase in body temperature also tend to show a smaller decrease in production under heat stress. However, because of the non-unity correlation between the two types of indicators of heat tolerance, both sources of information, productive and physiological ought to be taken into account to ensure the long-term sustainability of selection programmes aiming at improving productive levels when heat stress is a concerning issue.


Assuntos
Transtornos de Estresse por Calor , Doenças dos Ovinos , Termotolerância , Ovinos , Animais , Feminino , Lactação , Fazendas , Umidade , Transtornos de Estresse por Calor/veterinária , Transtornos de Estresse por Calor/metabolismo , Leite/metabolismo , Resposta ao Choque Térmico , Temperatura Alta
11.
ACS Sens ; 7(11): 3501-3512, 2022 Nov 25.
Artigo em Inglês | MEDLINE | ID: mdl-36368004

RESUMO

Triethylamine (TEA) is a serious threat to people's health, and it is still a challenge to detect TEA at ppb level near room temperature (RT). Herein, we developed a simple, low-cost, low-temperature, and ultra-sensitive TEA sensor based on Pd-SnO2/In2O3 composites. First, SnO2 nanoparticles were obtained by the pyrolysis of Sn-MOF@SnO2 precursor (MOF: metal organic framework), and Pd-SnO2/In2O3 composites were prepared by further compounding and doping. The results show that the Pd-SnO2/In2O3 sensor is highly sensitive to TEA gas at near RT (at 60 °C, the sensor response to 10 ppm TEA is 12,000, the response/recovery (res/rec) time is 51 s/493 s, and at 30 °C, the response value also reaches 1380, the res/rec time is 66 s/610 s), along with good selectivity, stability, and moisture resistance. Even at 10 °C operating temperature and 75% relative humidity (RH) in a low-temperature and high-humidity environment, it still maintains a high sensitivity of over 1000 to 10 ppm TEA, which shows great application potential in TEA detection. The reason for the enhanced performance of the 0.5%Pd-SnO2/In2O3 sensor can be attributed to a large number of adsorbed oxygens on the unique structure of the material, the good charge transfer ability of the n-n-type heterojunction between SnO2 and In2O3, the chemical sensitization and electronic sensitization of Pd nanoparticles, and the catalytic spillover effect. This work will provide a new approach for preparing sensors with good comprehensive properties, making full use of the advantages of the material structure-activity relationship.


Assuntos
Temperatura , Humanos , Umidade , Catálise
12.
Science ; 378(6622): 909-915, 2022 11 25.
Artigo em Inglês | MEDLINE | ID: mdl-36423296

RESUMO

Water is essential for survival, but one in three individuals worldwide (2.2 billion people) lacks access to safe drinking water. Water intake requirements largely reflect water turnover (WT), the water used by the body each day. We investigated the determinants of human WT in 5604 people from the ages of 8 days to 96 years from 23 countries using isotope-tracking (2H) methods. Age, body size, and composition were significantly associated with WT, as were physical activity, athletic status, pregnancy, socioeconomic status, and environmental characteristics (latitude, altitude, air temperature, and humidity). People who lived in countries with a low human development index (HDI) had higher WT than people in high-HDI countries. On the basis of this extensive dataset, we provide equations to predict human WT in relation to anthropometric, economic, and environmental factors.


Assuntos
Estilo de Vida , Água , Feminino , Gravidez , Humanos , Umidade , Exercício Físico , Classe Social
13.
Sensors (Basel) ; 22(19)2022 Sep 24.
Artigo em Inglês | MEDLINE | ID: mdl-36236341

RESUMO

The emerging use of low-temperature plasma in medicine, especially in wound treatment, calls for a better way of documenting the treatment parameters. This paper describes the development of a mobile sensory device (referred to as MSD) that can be used during the treatment to ease the documentation of important parameters in a streamlined process. These parameters include the patient's general information, plasma source device used in the treatment, plasma treatment time, ambient humidity and temperature. MSD was developed as a standalone Raspberry Pi-based version and attachable module version for laptops and tablets. Both versions feature a user-friendly GUI, temperature-humidity sensor, microphone, treatment report generation and export. For the logging of plasma treatment time, a sound-based plasma detection system was developed, initially for three medically certified plasma source devices: kINPen® MED, plasma care®, and PlasmaDerm® Flex. Experimental validation of the developed detection system shows accurate and reliable detection is achievable at 5 cm measurement distance in quiet and noisy environments for all devices. All in all, the developed tool is a first step to a more automated, integrated, and streamlined approach of plasma treatment documentation that can help prevent user variability.


Assuntos
Computadores de Mão , Microcomputadores , Documentação , Humanos , Umidade , Temperatura
14.
Sensors (Basel) ; 22(19)2022 Sep 26.
Artigo em Inglês | MEDLINE | ID: mdl-36236383

RESUMO

Low-cost sensors can provide inaccurate data as temperature and humidity affect sensor accuracy. Therefore, calibration and data correction are essential to obtain reliable measurements. This article presents a training and testing method used to calibrate a sensor module assembled from SO2 and NO2 electrochemical sensors (Alphasense B4 and B43F) alongside air temperature (T) and humidity (RH) sensors. Field training and testing were conducted in the industrialized coastal area of Quintero Bay, Chile. The raw responses of the electrochemical (mV) and T-RH sensors were subjected to multiple linear regression (MLR) using three data segments, based on either voltage (SO2 sensor) or temperature (NO2). The resulting MLR equations were used to estimate the reference concentration. In the field test, calibration improved the performance of the sensors after adding T and RH in a linear model. The most robust models for NO2 were associated with data collected at T < 10 °C (R2 = 0.85), while SO2 robust models (R2 = 0.97) were associated with data segments containing higher voltages. Overall, this training and testing method reduced the bias due to T and HR in the evaluated sensors and could be replicated in similar environments to correct raw data from low-cost electrochemical sensors. A calibration method based on training and sensor testing after relocation is presented. The results show that the SO2 sensor performed better when modeled for different segments of voltage data, and the NO2 sensor model performed better when calibrated for different temperature data segments.


Assuntos
Poluentes Atmosféricos , Dióxido de Nitrogênio , Poluentes Atmosféricos/análise , Calibragem , Monitoramento Ambiental , Umidade , Dióxido de Nitrogênio/análise
15.
Sensors (Basel) ; 22(19)2022 Sep 26.
Artigo em Inglês | MEDLINE | ID: mdl-36236405

RESUMO

Sensitive H2 sensors at low concentrations and room temperature are desired for the early warning and control of hydrogen leakage. In this paper, a resistive sensor based on Pt-doped In2O3 nanoparticles was fabricated using inkjet printing process. The H2 sensing performance of the sensor was evaluated at low concentrations below 1% at room temperature. It exhibited a relative high response of 42.34% to 0.6% H2. As the relative humidity of 0.5% H2 decreased from 34% to 23%, the response decreased slightly from 34% to 23%. The sensing principle and the humidity effect were discussed. A dynamic current sensing model for dry H2 detection was proposed based on Wolkenstein theory and experimentally verified to be able to predict the sensing behavior of the sensor. The H2 concentration can be calculated within a short measurement time using the model without waiting for the saturation of the response, which significantly reduces the sensing and recovery time of the sensor. The sensor is expected to be a promising candidate for room-temperature H2 detection, and the proposed model could be very helpful in promoting the application of the sensor for real-time H2 leakage monitoring.


Assuntos
Hidrogênio , Nanopartículas , Umidade , Temperatura
16.
Sensors (Basel) ; 22(19)2022 Oct 06.
Artigo em Inglês | MEDLINE | ID: mdl-36236680

RESUMO

Composites of functionalized single walled carbon nanotubes (SWCNTs) and gold nanoparticles (Au NPs) of ≈15 nm diameter were drop-cast on a printed circuit board (PCB) substrate equipped with interdigitated electrodes to make a hybrid thin film. Addition of Au NPs decorated the surface of SWCNTs networked films and acted as catalysts which resulted into an enhanced sensitivity and low ppb concentration detection limit. The compositions of the film were characterized by scanning electron microscope (SEM). SWCNTs clusters were loaded with various amount of Au NPs ranging from 1-10% (by weight) and their effect on Nitric oxide (NO) sensitivity was studied and optimized. Further, the optimized composite films were tested in both air and nitrogen environments and as well as over a wide relative humidity range (0-97%). Sensors were also tested for the selectivity by exposing to various gases such as nitrous oxide, ammonia, carbon monoxide, sulfur dioxide and acetone. Sensitivity to NO was found much higher than the other tested gases. The advantage of this sensor is that it is sensitive to NO at low ppb level (10 ppb) with estimated response time within 10 s and recovery time around 1 min, and has excellent reproducibility from sensor to sensor and works within the wide range of relative humidity (0-97%).


Assuntos
Nanopartículas Metálicas , Nanotubos de Carbono , Acetona , Amônia , Monóxido de Carbono , Eletrodos , Ouro/química , Umidade , Nanopartículas Metálicas/química , Nanotubos de Carbono/química , Óxido Nítrico , Nitrogênio , Óxido Nitroso , Reprodutibilidade dos Testes , Dióxido de Enxofre
17.
PLoS One ; 17(10): e0275841, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36240216

RESUMO

Learning techniques involve unraveling regression structures, which aim to analyze in a probabilistic frame the associations across variables of interest. Thus, analyzing fraction and/or proportion data may not be adequate with standard regression procedures, since the linear regression models generally assume that the dependent (outcome) variable is normally distributed. In this manner, we propose a statistical model called unit-Lindley regression model, for the purpose of Statistical Process Control (SPC). As a result, a new control chart tool was proposed, which targets the water monitoring dynamic, as well as the monitoring of relative humidity, per minute, of Copiapó city, located in Atacama Desert (one of the driest non-polar places on Earth), north of Chile. Our results show that variables such as wind speed, 24-hour temperature variation, and solar radiation are useful to describe the amount of relative humidity in the air. Additionally, Information Visualization (InfoVis) tools help to understand the time seasonality of the water particle phenomenon of the region in near real-time analysis. The developed methodology also helps to label unusual events, such as Camanchaca, and other water monitoring-related events.


Assuntos
Água , Tempo (Meteorologia) , Umidade , Temperatura , Vento
18.
Front Public Health ; 10: 1029390, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36249236

RESUMO

Recently, indoor thermal comfort has received more scholarly attention than ever due to the COVID-19 pandemic and global warming. However, most studies on indoor thermal comfort in China concentrated on urban buildings in the east and north. The indoor thermal comfort of rural dwellers in southwest China is insufficiently investigated. Hence, this study assesses residents' indoor thermal comfort in a rural dwelling in Linshui, obtains the thermal neutral temperature of the rural area, and analyzes the thermal adaptation behavior of rural dwellers. The results reveal that the thermal neutral temperature of rural dwellers is 29.33°C (operative temperature), higher than that presented in previous studies based on the same climate region. Indoor thermal conditions in rural dwellings are relatively harsh, but various thermal adaptation behavior of rural dwellers significantly improve their ability to withstand the harsh conditions. When people live in an environment with a (relatively) constant climate parameter (e.g., humidity), their perception of that parameter seems compromised. Most rural dwellers are unwilling to use cooling equipment with high energy consumption. Therefore, more passive cooling measures are recommended in the design and renovation of rural dwellings.


Assuntos
COVID-19 , Pandemias , COVID-19/epidemiologia , China , Humanos , Umidade , Temperatura
19.
Nat Commun ; 13(1): 6125, 2022 Oct 17.
Artigo em Inglês | MEDLINE | ID: mdl-36253413

RESUMO

Phthalate esters (PAEs) have been extensively used as additives in plastics and wallcovering, causing severe environmental contamination and increasing public health concerns. Here, we find that hematite nanoparticles with specific facet-control can efficiently catalyze PAEs hydrolysis under ambient humidity conditions, with the hydrolysis rates 2 orders of magnitude higher than that in water saturated condition. The catalytic performance of hematite shows a significant facet-dependence with the reactivity in the order {012} > {104} ≫ {001}, related to the atomic array of surface undercoordinated Fe. The {012} and {104} facets with the proper neighboring Fe-Fe distance of 0.34-0.39 nm can bidentately coordinate with PAEs, and thus induce much stronger Lewis-acid catalysis. Our study may inspire the development of nanomaterials with appropriate surface atomic arrays, improves our understanding for the natural transformation of PAEs under low humidity environment, and provides a promising approach to remediate/purify the ambient air contaminated by PAEs.


Assuntos
Ésteres , Ácidos Ftálicos , China , Etilaminas , Compostos Férricos , Umidade , Hidrólise , Plásticos , Água
20.
J Therm Biol ; 109: 103330, 2022 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-36195400

RESUMO

The promotion of China's National Fitness Program has caused an upsurge in the construction of outdoor sports venues and sparked an interest in research on the thermal comfort of people exercising outside. The design of exercise facilities and parks is usually function-oriented, and the spatial layout and arrangement of exercise paths are based on the exercise type. However, few studies compared the thermal comfort of different exercise types. This study investigated seasonal differences in thermal sensation, thermal comfort, and other influencing factors among people who engaged in various types of exercise in a severe cold city in China. The results showed significant differences in thermal comfort among the different exercise types. The acceptable thermal range of exercising people is greater than that of the resting ones. In the cold season, the thermal comfort of different exercise types had a significant correlation with thermal sensation, but not with humidity and wind sensations. On the other hand, the thermal comfort of jogging respondents was more affected by humidity, wind, and sun sensations during the hot season. The modified UTCI range of thermal stress category was proposed as a design reference for the thermal environment of outdoor exercise venues. Overall, this study can help enrich and guide outdoor thermal comfort research in severe cold regions and aid the design of urban exercise spaces.


Assuntos
Sensação Térmica , Vento , Cidades , Humanos , Umidade , Estações do Ano , Temperatura
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