Rainy Weather Conditions Research Articles

Growth analysis of sweet chestnut burr in two seasons with differing weather conditions

In Italy, most of the traditional sweet chestnut (Castanea sativa Mill.) orchards are still non-irrigated since they are located in mountain-hill areas with climate conditions that used to be optimal to sustain the vegetative and reproductive growth of this nut tree species. Nowadays, the increase of summer temperatures and the decrease of rainfall (due to climate change) are affecting negatively chestnut physiological performances. The aim of this experiment was to study sweet chestnut burr growth in two seasons, one warm/dry and one mild/rainy (2017 and 2018, respectively). The study was carried out in a traditional rainfed chestnut orchard. The seasonal burr growth was measured weekly from 30 days after full bloom (DAFB) to the beginning of burr valves opening. Air temperature and daily precipitation were measured at a nearby weather station. The results of this study highlighted that chestnut burr growth seems to be affected by seasonal weather conditions. Indeed, in 2017, the high summer temperatures and the moderate rainfall in summer (227 mm) and winter-spring (385 mm) appeared to affect negatively burr absolute growth rate (AGR; 0.31 mm day-1 ) and consequently final burr size (46.2 mm). The mild and rainy weather conditions that occurred in 2018 (663 and 340 mm of winter-spring and summer precipitation, respectively) positively influenced burr AGR (0.54 mm day-1 ) and therefore its final size (60.8 mm). These preliminary results suggest that the introduction of irrigation as a common management practice for chestnut orchards may promote their resilience to climate change with a positive effect on their productivity and fruit quality.

Optimization of the floating-type seaweed dryer

A floating-type solar dryer was designed and fabricated in order to answer the need for a faster and more efficient drying of seaweeds. Based on the results of the several field tests conducted, the developed seaweed dryer was capable of producing good quality dried seaweed products at a shorter drying time as compared to the traditional solar drying methods employed by seaweed farmers. The developed seaweed dryer was likewise proven to be highly adaptable to varying weather conditions. However, like most solar-type dryers, the performance of the fabricated seaweed dryer is greatly affected by weather variations. On a good sunny day, short drying time is expected unlike in cloudy or rainy weather conditions and even during nighttime where air drying can be done, the longer drying period is anticipated. Due to the different drying environments, the optimal dryer settings both for the daytime and cloudy or nighttime conditions must be determined. The optimization study conducted focused on the effects of varying the air inlet of the dryer by opening the foldable sidings to different height levels and the timely operation of exhaust fans in maximizing the combined effect of solar and air drying. An eight-hour drying test was conducted to determine the amount of moisture removed from the seaweed samples which was measured at 30 min interval. The analysis revealed that fully-opened sidings without running exhaust fans setting resulted in the highest moisture reduction in nighttime conditions. On the other hand, the sidings which were opened one-fourth from the bottom without running exhaust fans and sidings half-opened with running exhaust fans settings yielded the highest moisture reduction in daytime condition. In addition, no significant interaction was found between the level of sidings height openings and the operation of the exhaust fans during the nighttime condition. Conversely, there was a significant interaction between the level of sidings height openings and the operation of exhaust fans during the daytime condition.

Improving Lateral Autonomous Driving in Snow-Wet Environments Based on Road-Mark Reconstruction Using Principal Component Analysis

Lateral localization is a very sensible factor for evaluating the performance of autonomous driving. This paper addresses the general reasons of the lateral drifting by analyzing the performance of an accurate localization system at level of 10∼20 cm. The performance drops into 0.4∼3 m in winter because of the snow and wet road surface representations in the LIDAR data. Accordingly, we prove that enhancing the quality of online LIDAR data before calculating the matching score with the map is a key-solution to improve the lateral accuracy. This can be achieved by filtering-out snow, regenerating the road edges at correct positions and sharping-up the lane lines. To achieve these objectives, we propose a machine learning based road-mark reconstruction framework. The map images are converted into edge profiles to represent the road-marks in a series of peaks. Principal Component Analysis (PCA) is used to model the relationships between these peaks and extract the dominant distribution patterns. Based on the leading eigenvectors (eigenroads), the LIDAR edge profiles are safely and efficiently reconstructed during the autonomous driving. The reliability of the proposed framework has been tested using map data generated in 2015 and LIDAR data collected in 2016 and 2017 in snowy and rainy weather conditions. The experimental results have verified the robustness and truthfulness of the proposed framework to significantly improve the lateral accuracy in the LIDAR based localization systems. The localization accuracy has been enhanced to be 96.4% for 15 cm average error in very critical situations of changing the road patterns and the environmental conditions. The reliability of the proposed framework has been tested using map data generated in 2015 and LIDAR data collected in 2016 and 2017 in snowy and rainy weather conditions. The experimental results have verified the robustness and truthfulness of the proposed framework to significantly improve the lateral accuracy in the LIDAR based localization systems. The localization accuracy has been enhanced to be 96.4% for 15 cm average error in very critical situations of changing the road patterns and the environmental conditions.

Jemuran Otomatis Menggunakan Sensor LDR, Sensor Hujan Dan Sensor Kelembaban Berbasis Arduino Uno

The condition of weather changes in Indonesia is uncertain, so it difficult to predict clear and rainy weather. This is still a major problem for people who are drying clothes especially in the rainy weather conditions. Usually clothes is often left out traveling, with weather conditions like this make some people feel anxious because they do not have time to lift the clothesline in the rainy weather conditions. To overcome these problems the authors make an automatic clothesline prototype using LDR sensor, rain sensor, and moisture sensor using Arduino Uno. In addition to these sensors there are also additional such as fans and DC motors. From the results of testing tools that have been made tools can work well. The tool can work when the sensor will read the weather around, LDR sensor and rain sensor function to detect the weather around, while the humidity sensor serves to detect the condition of the clothes whether in wet or dry conditions.

A Survey of Weaver-birds’ Crop-raiding Behavioral Activity in Buea Municipality, Southwest Region, Cameroon

The entire surface of the earth is visited by the birds in view of their aerial flights and variable habitats in search of suitable breeding and feeding grounds. Flight, intelligence, adaptability and sight are some of the attributes that add to the diversity in the life of birds, consequently there is complexity in their overall behavioral pattern. The key objective of this study was to assess the weaver-bird crop-raiding activity in Buea municipality on different environmental parameters. The study was undertaken for three months, six days in a week, from 7:00am to 6:00pm. Scan observations were made on birds’ activity on a five-minute interval period across the entire study area. Simultaneously, data was collected on the environmental conditions. The study recorded a significant association between weaver-bird activity on crop-land, X2 = 11.653 df=14, P < 0.005 and X2 = 3.441 df=4, P<0.05 respectively. There was weaver-bird activity frequency of 51.63%, 45.35%, and 3.02% for Ploceus luteolus, Ploceus cuculatus, and Ploceus melanocephalus respectively. Moreover, a week association between bird activity and weather, X2 = 3.125 df=3, P<0.05 was recorded. The sunny and cloudy weather conditions recorded 53.26%, and 42.09% respectively, while the windy and rainy weather conditions were significantly low (3.26%). An association was recored between atmospheric conditions and weaver-birds’ activity on crops, X2 = 23.249 df=21, P<0.05. In addition, the most destroyed farms were Elaeis guineensis (32.33%), Saccharum officinarum (19.77%), Zea mays (17.44%), and Mangifera indica (15.58%) respectively, and the scale of destruction was very prominent on the foliage used by the birds for nest-building. Maize crops and oil-palms were among the crop species most subjected to destruction by birds. These crops were observed with poor foliage formation and fruits, consequently they withered, and since the local farming population in this municipality predominantly cultivate these crops most, a heavy toll is often taken on the annual farmers’ income.

Weaver-Birds’ crop-Raiding Behavior in Buea municipality, Southwest Region, Cameroon

The entire surface of the earth is visited by the birds in view of their aerial flights and variable habitats in search of suitable breeding and feeding grounds. Flight, intelligence, adaptability and sight are some of the attributes that add to the diversity in the life of birds, consequently there is complexity in their overall behavioral pattern. The key objective of this study was to assess the weaver-bird crop-raiding activity in Buea municipality on different environmental parameters. The study was undertaken for three months, six days in a week, from 7:00am to 6:00pm. Scan observations were made on birds’ activity on a five-minute interval period across the entire study area. Simultaneously, data was collected on the environmental conditions. The study recorded a significant association between weaver-bird activity on crop-land, X2 = 11.653 df=14, P &lt; 0.005 and X2 = 3.441 df=4, P&lt;0.05 respectively. There was weaver-bird activity frequency of 51.63%, 45.35%, and 3.02% for Ploceus luteolus, Ploceus cuculatus, and Ploceus melanocephalus respectively. Moreover, a week association between bird activity and weather, X2 = 3.125 df=3, P&lt;0.05 was recorded. The sunny and cloudy weather conditions recorded 53.26%, and 42.09% respectively, while the windy and rainy weather conditions were significantly low (3.26%). An association was recored between atmospheric conditions and weaver-birds’ activity on crops, X2 = 23.249 df=21, P&lt;0.05. In addition, the most destroyed farms were Elaeis guineensis (32.33%), Saccharum officinarum (19.77%), Zea mays (17.44%), and Mangifera indica (15.58%) respectively, and the scale of destruction was very prominent on the foliage used by the birds for nest-building. Maize crops and oil-palms were among the crop species most subjected to destruction by birds. These crops were observed with poor foliage formation and fruits, consequently they withered, and since the local farming population in this municipality predominantly cultivates these crops most, a heavy toll is often taken on the annual farmers’ income.

Flood Damage Area Detection Method by Means of Coherency Derived from Interferometric SAR Analysis with Sentinel-A SAR

Flood damage area detection method by means of coherency derived from interferometric SAR analysis with Sentinel-A SAR is proposed. One of the key issues for flooding area detection is to estimate it as soon as possible. The flooding area due to heavy rain, typhoon, severe storm, however, is usually covered with clouds. Therefore, it is not easy to detect with optical imagers onboard remote sensing satellite. On the other hand, Synthetic Aperture Radar: SAR onboard remote sensing satellites allows to observe the flooding area even if it is cloudy and rainy weather conditions. Usually, flooding area shows relatively small back scattering cross section due to the fact that return signal from the water surface is quite small because of dielectric loss. It, however, is not clear enough of the flooding area detected by using return signal of SAR data from the water surface. The proposed method uses coherency derived from interferometric SAR analysis. Through experiment, it is found that the proposed method is useful to detect the flooding area clearly.

The Dilemma of Road Safety in the Eastern Province of Saudi Arabia: Consequences and Prevention Strategies.

Road traffic crashes (RTCs) are one of the most critical public health problems worldwide. The WHO Global Status Report on Road Safety suggests that the annual fatality rate (per 100,000 people) due to RTCs in the Kingdom of Saudi Arabia (KSA) has increased from 17.4 to 27.4 over the last decade, which is an alarming situation. This paper presents an overview of RTCs in the Eastern Province, KSA, from 2009 to 2016. Key descriptive statistics for spatial and temporal distribution of crashes are presented. Statistics from the present study suggest that the year 2012 witnessed the highest number of crashes, and that the region Al-Ahsa had a significantly higher proportion of total crashes. It was concluded that the fatality rate for the province was 25.6, and the mean accident to injury ratio was 8:4. These numbers are substantially higher compared to developed countries and the neighboring Gulf states. Spatial distribution of crashes indicated that a large proportion of severe crashes occurred outside the city centers along urban highways. Logistic regression models were developed to predict crash severity. Model estimation analysis revealed that crash severity can be attributed to several significant factors including driver attributes (such as sleep, distraction, overspeeding), crash characteristics (such as sudden deviation from the lane, or collisions with other moving vehicles, road fences, pedestrians, or motorcyclists), and rainy weather conditions. After critical analysis of existing safety and infrastructure situations, various suitable crash prevention and mitigation strategies, for example, traffic enforcement, traffic calming measures, safety education programs, and coordination of key stakeholders, have been proposed.

Analysing drivers’ stop and go decisions in dilemma zones at signalised intersections

Drivers usually experience dilemmas in stopping or crossing at the end of a green phase or the first seconds of a red phase. These decisions could be the function of drivers’ behaviour. The severity of drivers’ behaviour while crossing intersections can be related to different factors such as traffic, environment and geometric conditions of the intersection. The primary objective of this study is to identify and analyse drivers’ behaviour while crossing signalised intersections. The required data were collected from four signalised intersections in Qazvin, Iran using video surveillance cameras in peak and off-peak hours and also in rainy and sunny weather conditions. More than 700 samples were observed, and drivers’ crossing behaviours were analysed using ordered and multinomial logit models after the onset of each yellow phase. The results showed that the speed of drivers who crossed during red and yellow phases was 39% and 13%, respectively, greater than drivers who stopped at this interval. The results indicated that the waiting time and the traffic volume at each red phase increase the driver's go decision when crossing the intersection. Furthermore, it was found that, in more congested conditions, the likelihood of crossing at yellow and red phases increases.

Mapping sugarcane in complex landscapes by integrating multi-temporal Sentinel-2 images and machine learning algorithms

Sugarcane is an important type of cash crop and plays a crucial role in global sugar production. Clarifying the magnitude of sugarcane planting will likely provide very evident supports for local land use management and policy-making. However, sugarcane growth environment in complex landscapes with frequent rainy weather conditions poses many challenges for its rapid mapping. This study thus tried and used 10-m Sentinel-2 images as well as crop phenology information to map sugarcane in Longzhou county of China in 2018. To minimize the influences of cloudy and rainy conditions, this study firstly fused all available images in each phenology stage to obtain cloud-free remote sensing images of three phenology stage (seedling, elongation and harvest) with the help of Google Earth Engine platform. Then, the study used the fused images to compute the normalized difference vegetation index (NDVI) of each stage. A three-band NDVI dataset along with 4000 training samples and 2000 random validation samples was finally used for sugarcane mapping. To assess the robustness of the three-band NDVI dataset with phenological characteristics for sugarcane mapping, this study employed five classifiers based on machine learning algorithms, including two support vector machine classifiers (Polynomial-SVM and RBF-SVM), a random forest classifier (RF), an artificial neural network classifier (ANN) and a decision tree classifier (CART-DT). Results showed that except for ANN classifier, Polynomial-SVM, RBF-SVM, RF and CART-DT classifiers displayed high accuracy sugarcane resultant maps with producer’s and user’s accuracies of greater than 91%. The ANN classifier tended to overestimate area of sugarcane and underestimate area of forests. Overall performances of five classifiers suggest Polynomial-SVM has the best potential to improve sugarcane mapping at the regional scale. Also, this study observed that most sugarcane (more than 75% of entire study area) tends to grow in flat regions with slope of less than 10°. This study emphasizes the importance of considering phenology in rapid sugarcane mapping, and suggests the potential of fine-resolution Sentinel-2 images and machine learning approaches in high-accuracy land use management and decision-making.

Simulation of Comparison from NRZ and RZ Pulse in Free Space Optics with Different Weather Conditions

FSO (Free Space Optic) is a form of optical technology communication by transmitting light to media free space. In the FSO system, the data transmission can be larger, namely 1-100 Gbps, and this is due to the large bandwidth width. FSO runs at a wavelength of 850 nm and 1550 nm. FSO is usually with a maximum distance of 2-4 km. This paper simulates the FSO optical transmission system using NRZ and RZ line coding in bright and rainy weather conditions. The parameters analyzed are Eye diagram, Optical Spec-trum, photocurrent, and received signal power. In the FSO line coding system, NRZ has an eye height value, received signal power and received photocurrent is greater than the RZ line coding at a distance of 1 km and 5 km in bright and rainy conditions. In the trial of this FSO communication system, it is better to use it at a distance of 1 km, because the received signal power is above 20 dBm and received photocurrent is still above 800 mA for NRZ and RZ line coding. This is due to the attenuation value of sunny weather conditions that are smaller between 0.2-3 dB/km, while in rain conditions between 4-17 dB/km.

A new method to determine the aerosol optical properties from multiple-wavelength O&amp;lt;sub&amp;gt;4&amp;lt;/sub&amp;gt; absorptions by MAX-DOAS observation

Abstract. Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observation was carried out from November 2016 to February 2017 in Beijing, China, to measure the O4 absorptions in UV and visible bands and further to illustrate its relationship with aerosol optical properties (AOPs) under different weather types. According to relative humidity, visibility, and PM2.5, we classified the observation periods into clear, light-haze, haze, heavy-haze, fog, and rainy weather conditions. There are obvious differences for measured AOPs under different weather conditions, especially scattering coefficient (σsca) and absorption coefficient (σsca). It was also found that both the O4 differential slant column densities (DSCDs) at the UV and visible bands varied in the order of clear days &gt; light-haze days &gt; haze days &gt; heavy-haze days &gt; fog days. The correlation coefficients (R2) between O4 DSCDs at 360.8 and 477.1 nm mainly varied in the order of clear days &gt; light-haze days &gt; haze days &gt; heavy-haze days. Based on the statistics of O4 DSCDs at an elevation angle 1∘ with the corresponding linear regression between UV and visible bands of segmental periods, the relationships between O4 DSCDs and AOPs were established. It should mainly be clear or light-haze days when the correlation slope is greater than 1.0, with a correlation coefficient (R2) greater than 0.9, and O4 DSCDs mainly greater than 2.5×1043 molec. cm−2. Meanwhile, σsca and σabs are less than 45 and 12 Mm−1, respectively. For haze or heavy-haze days, the correlation slope is less than 0.6, with an R2 less than 0.8, and O4 DSCDs mainly less than 1.3×1043 molec. cm−2, under which σsca and σabs are mainly located at 200–900 and 20–60 Mm−1. Additionally, the determination method was well validated based on another MAX-DOAS measurement at Gucheng from 19 to 27 November 2016. For more precise and accurate inversion of AOPs, more detailed look-up tables for O4 multiple-wavelength absorptions need to be developed. Since the ground surface AOPs were determined using MAX-DOAS observation at a 1∘ elevation in this study, we hope to highlight the potential of retrieved vertical spatially resolved AOPs being expected when multiple elevation angles of MAX-DOAS observation are used together.

Planktonic copepod community of a reef zone in the southern Gulf of Mexico

ABSTRACTIn this study, the variation of seasonal and inter-annual density and diversity of the copepod community in the Parque Nacional Sistema Arrecifal Veracruzano (PNSAV) was analysed. Samples were collected under nortes, rainy and dry weather conditions in 2011, as well as under nortes and dry weather conditions in 2012 and 2013 in four transects. Surface trawls with 330-μm conical nets were made. The temperature, salinity and dissolved oxygen were measured in situ. The values obtained were 23.07 ± 0.53 to 29.29 ± 0.27°C for temperature, 33.43 ± 0.49 to 35.91 ± 0.09 for salinity, and 2.52 ± 0.08 to 6.56 ± 0.08 mg l−1 for dissolved oxygen. The copepods collected belonged to 19 families, 28 genera and 62 species. Copepods represented between 69.74% and 76.79% of the abundance of crustaceans present in zooplankton. The highest number of copepods occurred under nortes weather conditions in 2011 with 401,885 ± 28,092 copepods/100 m3 of the species Temora stylifera. In 2012, 256,325 ± 76,872 copepods/100 m3 of the species Paracalanus aculeatus were obtained and in 2013, 311,526 ± 76,872 copepods/100 m3 of the species T. turbinata. The highest specific richness was found in the southern zone with 28 species. In 2013 the highest density was found in the northern zone with 100,323 ± 28,888 copepods/100 m3. The highest diversity was found under dry weather conditions in 2011 with 3.71 bits/individual. In the 3 years of study, 24 species were dominant; 12 of these, appeared in the 3 years of sampling: T. stylifera, T. turbinata, Labidocera scotti, P. aculeatus, O. latus, Pontellopsis villosa, Centropages velificatus, Parvocalanus crassirostris, Corycaeus speciosus, Undinula vulgaris, Oithona plumifera, and Farranula gracilis. Canonical correlation analysis showed the formation of five groups explained by the neritic or oceanic affinity of the species and their tolerance to changes in salinity or temperature.

KAITAN KETINGGIAN LAPISAN BATAS ATMOSFER DENGAN KONDISI CUACA BERDASARKAN PROFIL ANGIN VERTIKAL BERBASIS PENGAMATAN RADISONDE, RADAR CUACA DAN KELUARAN MODEL WRF-ARW

Lapisan Batas Atmosfer (LBA) merupakan bagian dari atmosfer paling bawah dimana medan aliran sangat dipengaruhi langsung oleh interaksi dengan permukaan bumi dan sensitif terhadap berbagai kondisi di permukaan bumi selama skala waktu singkat. Ketinggian LBA dapat bervariasi secara signifikan terhadap waktu akibat dari beberapa faktor termasuk dinamika skala luas, perawanan, percampuran konvektif dan variasi diurnal dari radiasi matahari. Di Indonesia, kajian mengenai LBA masih terbatas, sehingga kajian ini dilakukan untuk mengetahui hubungan antara ketinggian LBA dengan kondisi cuaca menggunakan metode profil vertikal angin dari data pengamatan (radar dan radiosonde) dan simulasi model numerik WRF-ARW. Hasilnya menunjukkan antara LBA dan kondisi cuaca hanya memiliki tingkat korelasi yang sedang dengan bias yang cukup besar dengan hasil pengamatan, namun simulasi keluaran model WRF-ARW dapat menggambarkan dengan cukup baik profil ketinggian LBA pada kondisi cuaca yang berbeda. Kondisi cuaca dapat mempengaruhi ketinggian LBA, dimana saat kondisi cuaca cerah, ketinggian LBA lebih tinggi jika dibandingkan dengan kondisi cuaca berawan atau hujan.

A generalized ordered probit model for analyzing driver injury severity of head-on crashes on two-lane rural highways in Malaysia

The number of fatal crashes in Malaysia has steadily been increasing, exceeding 7,000 deaths every year since 2016. Compared to other collision types, head-on crashes account for about 12% of total crashes in Malaysia yet are responsible for 17% of total fatal crashes. This indicates that head-on crashes are among the most fatal collision types. However, very few studies have been focused on the injury severity of head-on crashes. Therefore, this study aims to investigate the factors that are hypothesized to be associated with driver injury severity in head-on crashes. To do this, a generalized ordered probit (GOP) model was applied using 4-year (2009–2012) crash data collected on two-lane rural highways in Malaysia. The results show that the factors of dark not-lighted condition, horizontal curvature, heavy vehicle percentage, light vehicle traffic, posted speed limit, undulating terrain, improper overtaking maneuvers, not wearing seatbelt, and vehicle age contributed to more severe injuries, whereas rainy weather condition was found to be the only factor that was associated with less severe outcome. The findings of this study can help safety authorities understand the relationship between various risk factors and head-on crash severity.

Detection of critical safety events on freeways in clear and rainy weather using SHRP2 naturalistic driving data: Parametric and non-parametric techniques

A better understanding of what happened before and during a crash event could lead to development of countermeasures that reduce crash risk on freeways. This paper focused on detecting near-crashes on freeways by comparing environmental conditions and vehicle kinematics signatures of near-crash events to normal driving using data collected from the Second Strategic Highway Research Program (SHRP2) – Naturalist Driving Study. The study considered near-crash events as surrogate measures of crash risk only in rainy and clear weather conditions due to a limited number of near-crashes in other weather conditions. A time chunking technique was used with different aggregation levels to monitor changes in vehicle kinematics on a timescale. Both parametric and non-parametric techniques were used to detect near-crashes on freeways. The Binary Logistic Regression model was used as a parametric detection model, while Decision Tree , K-Nearest Neighbors (K-NN), and Deep Learning Artificial Neural Network were used as non-parametric detection models. The results showed that the logistic regression model provided a good fit of the input data and can detect near-crashes with outstanding discrimination. However, the time zone of interest identified by non-parametric models led to higher accurancy than that identified by the logistic regression model. In addition, Decision Tree and Deep Learning ANN machine learning algorithms showed higher detection accuracy of near-crashes compared to the K-NN algorithm.

PKM Kelompok Usaha Terasi Desa Bonang Kecamatan Lasem dalam Upaya Menghadapi Permasalahan Cuaca

The aim of the Community Partnership Program (PKM) is to increase community income through increased quality and quantity of shrimp paste production. This Partnership Program is business group of shrimp paste (rebon) in Bonang Village, Lasem Subdistrict, Rembang Regency with partners of shrimp paste craftsmen. The method carried out in the Community Partnership Program (PKM) is accompaniment to the group in understanding about the drying machine and get the information of capital provider. The realization of a drying machine that aims to ensure the continuity of the production process without having dependency by weather conditions and limited drying area. By using a shrimp paste drying machine, the group of shrimp paste craftsmen can still produce even in rainy and cloudy weather condition. The group of craftsmen can make product diversification, which is making ready-made cooked shrimp paste and be more hygienic by using shrimp paste drying machine.

Comparison of Mycobacterium ulcerans (Buruli ulcer) and Leptospira sp. (Leptospirosis) dynamics in urban and rural settings.

BackgroundZoonotic pathogens respond to changes in host range and/or pathogen, vector and host ecology. Environmental changes (biodiversity, habitat changes, variability in climate), even at a local level, lead to variability in environmental pathogen dynamics and can facilitate their transmission from natural reservoirs to new susceptible hosts. Whilst the environmental dynamics of aquatic bacteria are directly linked to seasonal changes of their habitat they also rely on the ecological processes underpining their transmission. However data allowing the comparison of these ecological processes are lacking. Here we compared the environmental dynamics of generalist and vector-borne aquatic bacterial pathogens in the same unit of time and space, and across rural and urban habitats in French Guiana (South America).Principal findingsUsing Leptospira sp. and Mycobacterium ulcerans we performed an environmental survey that allowed the detection of both pathogens in urban vs. rural areas, and during rainy vs. dry weather conditions. All samples were subjected to qPCR amplifications of LipL32 (Leptospira sp.) and IS2404 and KR (M. ulcerans) genetic markers. We found (i) a greater presence of M. ulcerans in rural areas compared with Leptospira sp., (ii) that modified urban environments were more favourable to the establishment of both pathogens, (iii) that Leptospira sp. presence was enhanced during the rainy season and M. ulcerans during the dry period, and (iv) differences in the spatial distribution of both bacteria across urban sites, probably due to the mode of dissemination of each pathogen in the environment.ConclusionsWe propose that in French Guiana simplified and modified urban ecosystems might favour leptospirosis and Buruli ulcer emergence and transmission. Moreover, disease risk was also constrained by seasonality. We suggest that the prevention of aquatic bacterial disease emergence in impoverished urban areas of developing countries would benefit from seasonal diseases targeted surveys, which would maximise limited budgets from cash-strapped health agencies.

The effect of straw mulch on nitrogen, phosphorus and potassium uptake and use in hybrid rice

To optimize straw application and understand the effects of straw mulch and straw nutrient release on rice nutrient uptake, we investigated the effects of two types of straw mulch (S1—wheat straw and S2—rapeseed straw) and no straw mulch (S0) on straw decomposition and nutrient release; rice growth and nutrient accumulation; and the nitrogen, phosphorus and potassium stimulation ratio and recovery efficiency of straw on rice in 2013 and 2014. Results showed that wheat straw mulch was associated with a higher decomposition ratio and total nutrient release and frequent rainfall could further increase decomposition and nutrient release in the 0–30 days after transplanting growth stage. Remarkably, the later stages were associated with decreased decomposition and nutrient release, especially on rapeseed straw mulch. Wheat and rapeseed straw mulch had obvious effects on rice growth and nutrient uptake. Compared with S0, S1 could distinctly promote dry matter accumulation and increase the levels of nitrogen, phosphorus and potassium in the rice plant at each growth stage, as well as increase grain yield in 2013 and 2014. By contrast, S2 inhibited rice growth; decreased nitrogen, phosphorus and potassium uptake and dry matter accumulation in rice plants during the early growth stage, while significantly improving that in the following growth stage; but decreased grain yield under rainy and cold weather conditions (2014). Compared with S0, wheat and rapeseed straw mulch increased total nitrogen, phosphorus and potassium accumulation in rice plants by 1.81–10.79%, 2.70–42.21% and 16.41–17.92%, respectively, thus improving nitrogen, phosphorus and potassium utilization.

Experimental Investigation and Applied Research of Permeable Marking for Porous Asphalt Wearing Course

Abstract Porous asphalt wearing courses are a type of high-performance wearing course with technical features such as high skid resistance and low noise, as well as abilities that inhibit water mist during rainy weather conditions, prevent skidding during high-speed driving, and alleviate dazzle light during night driving. With the gradual popularization of this high-performance wearing course in China, the problem of its matched markings has become a growing concern. Hot melting scrape coating markings are commonly used in porous asphalt wearing course designs. However, this marking technology has associated problems. For example, its application often blocks the pores of the porous asphalt and causes surface water to gather on rainy days. It also attenuates the functional properties of porous asphalt. Additionally, material consumption increases because of marking infiltration. The proposed permeable marking technology addresses issues of performance concerning drainability, high skid resistance, and all-dimensional and all-weather reflection. Technical problems, such as pore blockage from ordinary markings, are successfully resolved by using an active bicomponent marking material through its reaction into membranes and in combination with rotating-coating type or discontinuous-extrusion type marking application technology. From the laboratory and in situ tests, it was determined that adhesion, reflection in the dark, wet driving conditions, and pavement skid-resistance value from the marking are improved.