Miracle-dz/UniFAR-FTUs huggingface dataset:
Plant Traits Help Explain the Tight Relationship between Vegetation Indices and Gross Primary Production

Remotely-sensed Vegetation Indices (VIs) are often tightly correlated with terrestrial ecosystem CO2 uptake (Gross Primary Production or GPP). These correlations have been exploited to infer GPP at local to global scales and over half-hour to decadal periods, though the underlying mechanisms remain incompletely understood. We used satellite remote sensing and eddy covariance observations at 10 sites across a California climate gradient to explore the relationships between GPP, the Enhanced Vegetation Index (EVI), the Normalized Difference Vegetation Index (NDVI), and the Near InfraRed Vegetation (NIRv) index. EVI and NIRv were linearly correlated with GPP across both space and time, whereas the relationship between NDVI and GPP was less general. We explored these interactions using radiative transfer and GPP models forced with in-situ plant trait and soil reflectance observations. GPP ultimately reflects the product of Leaf Area Index (LAI) and leaf level CO2 uptake (Aleaf); a VI that is sensitive mainly to LAI will lack generality across ecosystems that differ in Aleaf. EVI and NIRv showed a strong, multiplicative sensitivity to LAI and Leaf Mass per Area (LMA). LMA was correlated with Aleaf, and EVI and NIRv consequently mimic GPP’s multiplicative sensitivity to LAI and Aleaf, as mediated by LMA. NDVI was most sensitive to LAI, and was relatively insensitive to leaf properties over realistic conditions; NDVI lacked EVI and NIRv’s sensitivity to both LAI and Aleaf. These findings carry implications for understanding the limitations of current VIs for predicting GPP, and also for devising strategies to improve predictions of GPP.
Growth Performance, Behaviour, Forestomach Development and Meat Quality of Veal Calves Provided With Barley Grain or Ground Wheat Straw For Welfare Purpose

Abstract Two different feeding plans for veal calves were compared in the study: a traditional liquid diet supplemented with 250 g/calf/d of barley grain or with 250 g/calf/d of ground wheat straw. The two solid feeds had different chemical composition but a similar particle size obtained by grinding the straw in a mill with an 8-mm mesh screen. Twenty-four Polish Friesian male calves were used in the study and they were housed in individual wooden stalls (0.83 x 1.80 m). The health status of all the calves was satisfactory for the entire fattening period and no specific medical treatment was required during the trial. Calves fed wheat straw showed a greater intake of solid feed (196 vs. 139 g/d; P<0.01) and a higher average daily gain (1288 vs. 1203 g/d; P<0.05) than those receiving barley grain. The consumption of milk replacer was not affected by the type of solid feed and no milk refusal episodes were detected. The haemoglobin concentration was similar in calves receiving the two feeding treatments despite the higher iron intake provided by the wheat straw throughout the fattening period (2.12 vs. 1.15 g; P<0.001). It is likely that the iron in wheat straw was less available for the calves’ metabolism. Feeding behaviour was affected by the provision of solid feeds. Eating and chewing were prolonged in calves receiving ground wheat straw and the same solid feed reduced the frequency of oral stereotypies at the end of the fattening period. At the slaughterhouse, no differences were observed between the feeding treatments as regards carcass weight and dressing percentage. The calves fed ground wheat straw had a heavier weight of the empty omasum (518 vs. 341 g; P<0.01) whereas the empty weight of the reticulorumen and abomasum were similar to those of calves fed barley grain. The incidence of abomasal erosions, ulcers and scars was similar in both treatments; however the index of abomasal damage, which considers the number and the seriousness of different type of lesions, was higher in calves receiving barley grain. Therefore, the grinding of straw particles, as opposed to barley grain, can reduce the abrasiveness of roughage at the abomasum level. Visual evaluation of the carcass colour and instrumental measurement of meat colour did not show significant differences between diets. The study confirmed that in the veal calf, carcass and meat colour are not strictly correlated with the iron intake from solid feeds.
Lead poisoning in swans and sources of contamination in Ireland

A study of blood levels in mute swans Cygnus olor in Ireland has revealed that ingested lead pellets are responsible for acute lead poisoning. Forty-two percent of blood samples from 890 live birds at one site showed elevated lead levels. X-ray examination of live birds revealed the source of contamination to be ingested lead pellets. Urban birds were shown to have higher (P 0001) lead levels than rural birds, the blood lead levels of which were presumed to reflect natural background levels. Urban grass was shown to have elevated lead but this did not cause lead poisoning in Canada geese Branta canadensis. Post-mortem examination has shown that 68% (n= 101) of all mute swans examined from a number of sites died from lead poisoning. Two sources of poisoning were identified; spent gunshot from a claypigeon shooting site at Lough Neagh, Northern Ireland, and lost or discarded anglers' weights at Cork Lough and at a fishing pond in Belfast, N.I. The first known case of lead poisoning in whooper swans Cygnus cygnus in Ireland is recorded which resulted from the ingestion of gunshot used almost two decades earlier. Aspects of the pathology of lead poisoned swans is discussed.
Tutorial 1B: AI Chip Technologies and DFT Methodologies

Hardware acceleration for Artificial Intelligence (AI) is now a very competitive and rapidly evolving market. In this tutorial, we will start by covering the basics of deep learning. We will proceed to give an overview of the new and exciting field of using AI chips to accelerate deep learning computations. It will cover the critical and special characteristics and the architecture of the most popular AI chips. Next we will summarize the features of the AI chips from design-for-test (DFT) perspective and introduce the DFT technologies that can help testing AI chips and speeding up time-to-market. Finally, we will present a few case studies on how DFT is implemented on the real AI chips.
Deep Learning Approaches Applied to Remote Sensing Datasets for Road Extraction: A State-Of-The-Art Review

One of the most challenging research subjects in remote sensing is feature extraction, such as road features, from remote sensing images. Such an extraction influences multiple scenes, including map updating, traffic management, emergency tasks, road monitoring, and others. Therefore, a systematic review of deep learning techniques applied to common remote sensing benchmarks for road extraction is conducted in this study. The research is conducted based on four main types of deep learning methods, namely, the GANs model, deconvolutional networks, FCNs, and patch-based CNNs models. We also compare these various deep learning models applied to remote sensing datasets to show which method performs well in extracting road parts from high-resolution remote sensing images. Moreover, we describe future research directions and research gaps. Results indicate that the largest reported performance record is related to the deconvolutional nets applied to remote sensing images, and the F1 score metric of the generative adversarial network model, DenseNet method, and FCN-32 applied to UAV and Google Earth images are high: 96.08%, 95.72%, and 94.59%, respectively.
Estimating Daily Inundation Probability Using Remote Sensing, Riverine Flood, and Storm Surge Models: A Case of Hurricane Harvey

Heavy precipitation and storm surges often co-occur and compound together to form sudden and severe flooding events. However, we lack comprehensive observational tools with high temporal and spatial resolution to capture these fast-evolving hazards. Remotely sensed images provide extensive spatial coverage, but they may be limited by adverse weather conditions or platform revisiting schedule. River gauges could provide frequent water height measurement but they are sparsely distributed. Riverine flood and storm surge models, depending on input data quality and calibration process, have various uncertainties. These lead to inevitable temporal and spatial gaps in monitoring inundation dynamics. To fill in the observation gaps, this paper proposes a probabilistic method to estimate daily inundation probability by combining the information from multiple sources, including satellite remote sensing, riverine flood depth, storm surge height, and land cover. Each data source is regarded as a spatial evidence layer, and the weight of evidence is calculated by assessing the association between the evidence presence and inundation occurrence. Within a Bayesian model, the fusion results are daily inundation probability whenever at least one data source is available. The proposed method is applied to estimate daily inundation in Harris, Texas, impacted by Hurricane Harvey. The results agree with the reference water extent, high water mark, and extracted tweet locations. This method could help to further understand flooding as an evolving time-space process and support response and mitigation decisions.
Differential Chromosome Banding and RAPD Analysis of Four Varieties of Capsicum frutescens L.

Summary Karyotype and RAPD analysis of four varieties of Capsicum frutescens L. (Chilli), namely BARI Chilli-1, Bogra Chilli, Binti Chilli, and Coarse Chilli, were conducted. These four varieties were found to possess 2 n =24 chromosomes. The total length of 2 n chromosome complement was highest (86.35 µ m) in the Coarse Chilli and lowest (38.57 µ m) in the Bogra Chilli. The centromeric formulae of these four varieties were different; they were 20 m+2 sm+2 ac for BARI Chilli-1, 21 m+3 sm for Bogra Chilli, 19 m+2 sm+3 ac for Binti Chilli, and 10 m+14 sm for Coarse Chilli. The range of individual chromosome length was largest (1.92–4.84 µ m) in the Coarse Chilli and smallest (0.84–2.22 µ m) in the Bogra Chilli. Heteromorphicity in respect of centromeric position in a member of pair XI of Bogra Chilli and Binti Chilli suggested the occurrence of deletion. Four CMA-bands were found in BARI Chilli-1 and Bogra Chilli, whereas two chromosomes of the Coarse Chilli entirely ﬂuoresced with CMA. No CMA band was found in the Binti Chilli. Each variety had a deﬁnite RAPD ﬁngerprinting pattern. The Coarse Chilli had several unique DNA fragments. Therefore, the four variety of Capsicum frutescens L. could be characterized with the help of karyotype and RAPD analysis.
Methods in Applied Soil Microbiology and Biochemistry

(Chapter Headings): Introduction. Quality Control and Quality Assurance in Applied Soil Microbiology and Biochemistry. Soil Sampling, Handling, Storage, And Analysis. Enrichment, Isolation and Counting of Soil Microorganisms. Estimation of Microbial Activities. Anaerobic Microbial Activities in Soil. Enzyme Activities. Micorbial Biomass. Community Structure. Field Methods. Bioremediation of Soil. Subject Index.
Evaluation of Satellite-Derived Surface Soil Moisture Products over Agricultural Regions of Canada

Soil moisture is a critical indicator for climate change and agricultural drought, but its measurement is challenging due to large variability with land cover, soil type, time, space and depth. Satellite estimates of soil moisture are highly desirable and have become more widely available over the past decade. This study investigates and compares the performance of four surface soil moisture satellite datasets over Canada, namely, Soil Moisture and Ocean Salinity Level 3 (SMOS L3), versions 3.3 and 4.2 of European Space Agency Climate Change Initiative (ESA CCI) soil moisture product and a recent product called SMOS-INRA-CESBIO (SMOS-IC) that contains corrections designed to reduce several known sources of uncertainty in SMOS L3. These datasets were evaluated against in situ networks located in mostly agricultural regions of Canada for the period 2012 to 2014. Two statistical comparison methods were used, namely, metrics for mean soil moisture and median of metrics. The results suggest that, while both methods show similar comparisons for regional networks, over large networks, the median of metrics method is more representative of the overall correlation and variability and is therefore a more appropriate method for evaluating the performance of satellite products. Overall, the SMOS products have higher daily temporal correlations, but larger biases, against in situ soil moisture than the ESA CCI products, with SMOS-IC having higher correlations and smaller variability than SMOS L3. The SMOS products capture daily wetting and drying events better than the ESA CCI products, with the SMOS products capturing at least 75% of observed drying as compared to 55% for the ESA CCI products. Overall, for periods during which there are sufficient observations, both SMOS products are more suitable for agricultural applications over Canada than the ESA CCI products, even though SMOS-IC is able to capture soil moisture variability more accurately than SMOS L3.
Macroparasite communities in European eels, Anguilla anguilla, from French Mediterranean lagoons, with special reference to the invasive species Anguillicola crassus and Pseudodactylogyrus spp.

European eel parasites, in particular invasive species, are suspected to play a role in the decline in the populations of their host. The aims of this work were to describe the parasitic fauna of eels in French Mediterranean lagoons and to study the epidemiological trends of the invasive helminth species, the nematode Anguillicola crassus and the monogenean Pseudodactylogyrus spp. , in regard to spatio-temporal dynamics, host biological characteristics and parasite community. A total of 418 eels was sampled in eight lagoons between March 2003 and June 2005. Our results revealed a total macroparasite richness of 23 species: 1 Monogenea, 13 Digenea, 2 Cestoda, 3 Nematoda, 2 Acantocephala and 2 Crustacea. We found no variation in A. crassus abundance in Salses-Leucate lagoon in the same month across years. However, the nematode abundance was higher in eels caught in summer than in those caught in winter. Pseudodactylogyrus sp. was not found in Salses-Leucate lagoon, except in July 2004. Comparisons between the lagoons on the same date showed that they could be separated into two groups for both species' abundance: Grau-du-Roi, Mauguio, Palavas and Vaccares lagoons, where abundance was rather high, against Bages-Sigean, Pierre-Blanche, Salses-Leucate and Thau lagoons, where abundance was rather low or nil. We found significant negative relationships between A. crassus abundance and the length and age of eels. We also found a significant positive relationship between A. crassus and Pseudodactylogyrus sp. abundance. Finally, our results showed significant positive relationships between both A. crassus and Pseudodactylogyrus sp. abundance and the abundance of the digeneans Prosorhynchus aculeatus and Lecithochirium gravidum . We discuss the results in regard to the dynamics of invasions, the characteristics of the parasite life cycles and the ecology of eels.
Mapping Fragmented Impervious Surface Areas Overlooked by Global Land-Cover Products in the Liping County, Guizhou Province, China

Imperviousness is an important indicator for monitoring urbanization and environmental changes, and is evaluated widely in urban areas, but not in rural areas. An accurate impervious surface area (ISA) map in rural areas is essential to achieve environmental conservation and sustainable rural development. Global land-cover products such as MODIS MCD12Q1, ESA CCI-LC, and Global Urban Land are common resources for environmental practitioners to collect land-cover information including ISAs. However, global products tend to focus on large ISA agglomerations and may not identify fragmented ISA extents in less populated regions. Land-use planners and practitioners have to map ISAs if it is difficult to obtain such spatially explicit information from local governments. A common and consistent approach for rural ISA mapping is yet to be established. A case study of the Liping County, a typical rural region in southwest China, was undertaken with the objectives of assessing the global land-cover products in the context of rural ISA mapping and proposing a simple and feasible approach for the mapping. This approach was developed using Landsat 8 imagery and by applying a random forests classifier. An appropriate number of training samples were distributed to towns or villages across all townships in the study area for classification. The results demonstrate that the global land-cover products identified major ISA agglomerations, specifically at the county seat; however, other fragmented ISAs over the study area were overlooked. In contrast, the map created using the developed approach inferred ISAs across all townships with an overall accuracy of 91%. A large amount of training samples together with geographic information of towns or villages is the key suggestion to identify and map ISAs in rural areas.
Integrated Landscape Change Analysis of Protected Areas and their Surrounding Landscapes: Application in the Brazilian Cerrado

Remote sensing tools have been long used to monitor landscape dynamics inside and around protected areas. Hereto, scientists have largely relied on land use and land cover (LULC) data to derive indicators for monitoring these dynamics, but these metrics do not capture changes in the state of vegetation surfaces that may compromise the ecological integrity of conservation areas’ landscapes. Here, we introduce a methodology that combines LULC change estimates with three Normalized Difference Vegetation Index-based proxy indicators of vegetation productivity, phenology, and structural change. We illustrate the utility of this methodology through a regional and local analysis of the landscape dynamics in the Cerrado Biome in Brazil in 2001 and 2016. Despite relatively little natural vegetation loss inside core protected areas and their legal buffer zones, the different indicators revealed significant LULC conversions from natural vegetation to farming land, general productivity loss, homogenization of natural forests, significant agricultural expansion, and a general increase in productivity. These results suggest an overall degradation of habitats and intensification of land use in the studied conservation area network, highlighting serious conservation inefficiencies in this region and stressing the importance of integrated landscape change analyses to provide complementary indicators of ecologically-relevant dynamics in these key conservation areas.
Change Detection in Aerial Images Using Three-Dimensional Feature Maps

Interest in aerial image analysis has increased owing to recent developments in and availability of aerial imaging technologies, like unmanned aerial vehicles (UAVs), as well as a growing need for autonomous surveillance systems. Variant illumination, intensity noise, and different viewpoints are among the main challenges to overcome in order to determine changes in aerial images. In this paper, we present a robust method for change detection in aerial images. To accomplish this, the method extracts three-dimensional (3D) features for segmentation of objects above a defined reference surface at each instant. The acquired 3D feature maps, with two measurements, are then used to determine changes in a scene over time. In addition, the important parameters that affect measurement, such as the camera’s sampling rate, image resolution, the height of the drone, and the pixel’s height information, are investigated through a mathematical model. To exhibit its applicability, the proposed method has been evaluated on aerial images of various real-world locations and the results are promising. The performance indicates the robustness of the method in addressing the problems of conventional change detection methods, such as intensity differences and shadows.
Offloading Decisions in a Mobile Edge Computing Node with Time and Energy Constraints

This article describes a simulated annealing based offloading decision with processing time, energy consumption and resource constraints in a Mobile Edge Computing Node. Edge computing mostly deals with mobile devices subject to constraints. Especially because of their limited processing capacity and the availability of their battery, these devices have to offload some of their heavy tasks, which require a lot of calculations. We consider a single mobile device with a list of heavy tasks that can be offloadable. The formulated optimization problem takes into account both the dedicated energy capacity and the total execution time. We proposed a heuristic solution schema. To evaluate our solution, we performed a set of simulation experiments. The results obtained in terms of processing time and energy consumption are very encouraging.
Recent advances in biomedical literature mining

The recent years have witnessed a rapid increase in the number of scientific articles in biomedical domain. These literature are mostly available and readily accessible in electronic format. The domain knowledge hidden in them is critical for biomedical research and applications, which makes biomedical literature mining (BLM) techniques highly demanding. Numerous efforts have been made on this topic from both biomedical informatics (BMI) and computer science (CS) communities. The BMI community focuses more on the concrete application problems and thus prefer more interpretable and descriptive methods, while the CS community chases more on superior performance and generalization ability, thus more sophisticated and universal models are developed. The goal of this paper is to provide a review of the recent advances in BLM from both communities and inspire new research directions.
IRB Policies for Obtaining Informed Consent from Non-English-Speaking People.

United States regulations for the protection of human research subjects prescribe parameters for documentation of valid informed consent, which include the stipulation that the process be in a "language understandable to the subject. " While significant energy has been devoted to improving the readability of consent documents, supplemental educational tools, and nuanced measurements of individual decisional capacity, there is little guidance about how to best meet the informational needs of adults with decisional capacity who do not speak English. This article reviews the institutional review board policies from the twenty-one research centers that received the most funding from the National Institutes of Health in 2018 and compares their guidelines for obtaining informed consent from non-English speakers. Inconsistent practices suggest the need for more assertive federal direction on what parameters constitute valid consent for this population. These practices also indicate a reluctance to directly engage the ethical underpinnings of consent policies for non-English speakers.