Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanistic modelling of cropland and grassland ecosystems: focus on the nitrogen cycle, the soil carbon and the management practices

After the presentation of the state of art about the importance to study the GHG emissions by terrestrial agroecosystem and the relation with the environmental conditions, the different ways to realized this study are presented. First, the different measurement methods are explained. Secondly, the principles of modelling are described followed by an history of the ecosystem models and the ways to classify them. Actually, the models have different objectives and consequently are composed differently. The model developed in the framework of this thesis aims to study the temporal dynamics (from intra-day to inter-annual) of the processes that compose the water, carbon and nitrogen cycle and lead to GHG exchanges between atmosphere and grasslands or croplands. According to those objectives, the model is a one dimension (vertical), dynamic and mechanistic model with a time step of 30 minutes. This model is called TADA, for Terrestrial Agro-ecosystem dynamics Analysis. It is created by using the forest model ASPECTS as a base, by adapting the processes that are specific to crop and grass ecosystems (e.g. phenology, carbon and nitrogen allocation, etc) and by implementing some new necessary process (e.g. management operation, grazing effect, etc). This project is a team work, the different parts of the code are divided by three for the modification, the implementation and the calibration. This thesis focuses on the soil organic carbon, the nitrogen cycle and the management operations. The carbon cycle and the phenology are presented in Delhez (2019) and the water cycle and grazing effect by Dumont (2019). Mineralization, humification and nitrification processes are calibrated in this work by using measurement data acquired on experimental sites located at Dorinne and Lonzée. The results show a lack of measurement data to calibrate the model correctly. After the calibration (including the calibration from the other thesis), the grassland version of the model runs to simulate the year 2013 at Dorinne and the cropland version to simulate the winter wheat crop of 2015 at Lonzée. The modelled results are discussed and compared to the measurement and to the literature. For the cropland, all the carbon fluxes are underestimate which could be a chain reaction due to one process, probably a too low leaf nitrogen content. For the grassland, the values are consistent with the measurements. The nitrous oxide fluxes modelled in the two ecosystems are in the order of magnitude of the value reported in the literature. Different proposals to ameliorate the model or to improve the calibration are then presented in regard with the different results reached.
VILLAGE INNOVATION THROUGH VILLAGE INFORMATION ADMINISTRATION SYSTEM (SAID) IN BONDOWOSO DISTRICT EAST JAVA PROVINCE

The Evaluation of Pilot Project Universitas Membangun Desa (UMD) focuses on the development of villages in Bondowoso district of East Java province through the innovation of the use of information technology. This study presents an evaluation of the implementation of a pilot project of the Village Information Administration System (SAID) implemented in ten villages located in two wringin and cermee sub districts in 2016. This program is an innovative collaboration between Jember University, Community Collaboration and welfare services (KOMPAK) and Australian Aid. The purpose of this program is to build a Village Information System (SID) and utilize it to create an independent village in data and information, introduction of village potential and marketing of village superior products. through a qualitative approach, this research can describe the context and setting naturally through observation, interviews with stakeholders and beneficiaries of the program. The results show that the Village Information Administration System (SAID) is able to accelerate and improve the quality of village government services but there are several problems in its implementation such as internet network problems, low human resource competence, lack of support from village government and inadequate facilities and infrastructure. Keywords: Village Information Administration System, Information Technology Innovation, Independent Village
Mosaic Management: The Missing Ingredient for Biodiversity Innovation in Urban Greenspace Design

With a new stream of studies adding to evidence revealing disturbing declines in global populations of insects (Hallmann et al. 2018, Lister & Garcia 2018, Sánchez-Bayo and Wyckhuys 2019) and reports of an ecological catastrophe on the scale of a sixth mass extinction, there is an urgent need to do more to conserve these species that underpin our ecosystems. Urban areas have the potential to provide a safe haven for many rare and declining species that have been extirpated from our rural landscapes by intensive agricultural practices (Benton et al. 2003). But only if we manage those safe havens appropriately!
Towards information system development for data extraction from web

Today, the Internet contains a huge number of sources of information, which is constantly used in our daily lives. It often happens that similar in meaning information is presented in different forms on different resources (for example, electronic libraries, online stores, news sites and etc.). In this paper, we analyze the extraction of information from certain type of web sources that is required by the user. The analysis of the data extraction problem was carried out. When considering the main approaches to data extraction, the strengths and weaknesses of each were identified. The main aspects of the extraction of web knowledge were formulated. Approaches and information technologies for solving problems of syntactic analysis based on existing information systems are analyzed. Based on the analysis, the task of developing models and software components for extracting data from certain types of web resources were solving. A conceptual model of extracting data was developed taking into account web space as an external data source. A requirements specification for the software component was created, which will allow to continue working on the project and to clearly understand the requirements and constraints for implementation. During the process of modeling software, the following diagrams have been developed, such as activities, sequences and deployments, which will then be used to create the finished software application. For further development of the software, a programming platform and types of testing (load and modular) were defined. The obtained results allow to state that the proposed design solution, which will be implemented as a prototype of the software system, can perform the task of extracting data from different sources on the basis of a single semantic template.
A characterization of a Southeast Florida stony coral assemblage after a disease event

IV Introduction . 1 Methods . 4 Stony coral demographic surveys . 4 Statistical analyses . 7 Results . 8 Increased coral disease and coral assemblage declines . 8 Species-specific effects . 14 Juvenile surveys . 20 Discussion . 27 Conclusions and recommendations . 30 Literature Cited . 33
PSI Meets Signal: Integrating a Malicious-Secure Private Contact Discovery Solution in an Open-Source Instant Messaging Service

Mobile messengers like WhatsApp have gained a lot of popularity in recent years. While their security is improving, e.g., with WhatsApp incorporating end-to-end encryption, many of them suffer from a lack of privacy. A prominent example for this is contact discovery. For users to find out, which of their contacts also use the messenger, many apps upload the user’s entire address book to their server, including information about people that do not use the messenger. Some messengers, like Signal, use private contact discovery, a use case of private set intersection (PSI). This allows users to find their friends while keeping any contacts, that do not use the messenger, private. Unfortunately, Signal uses a naive and insecure hashing-based PSI protocol that does not yield sufficient privacy protection. The results of a survey we conducted on ‘secure’ messengers, show that all of them provide little to no privacy during contact discovery. We look at two precomputation based PSI protocols that have previously been identified as candidates for efficient and private contact discovery. In both protocols, we reduce the communication required to inform clients about changes to the server’s database by up to four times. For one of the protocols, we nearly halve the online phase communication required for each of the user’s contacts. We also make both protocols secure against malicious clients. To demonstrate the practicality of our work, we integrate our implementation into the Signal messenger for Android.
Fennoscandian uplift study as an example of Russian-Finnish cooperation in Arctic geodesy (Advisory)

Today, the Arctic region is a fertile place for international scientific cooperation in the field of earth sciences. A positive example of such cooperation is a bilateral Russian-Finnish study in the field of geodesy carried out over two decades. The main object of the joint Russian-Finnish research is the post-glacial uplift of Fennoscandia. As a result of joint research, estimates of the velocities of the vertical movements of the earth’s crust in the Northeast part of the region have been obtained. Regional map of the recent vertical crustal movement is compiled. The results obtained are compared with the existing geophysical models and estimates of other authors. High-precision absolute measurements of the acceleration of gravity contribute to the independent control of the estimates of the speeds of the post-glacial uplift. Much attention is paid to the metrological control of measuring equipment. Bilateral and 1multilateral comparisons of absolute gravimeters are periodically performed. The paper briefly reviews the work carried out and the results obtained. International cooperation is expected to continue.
Prediction of a time series using regression by vector support machines

The Vector Support Machines (VSM) have their greatest application in the area of pattern recognition, for the solution of biclass and multiclass classification problems, however, they can also be used for the solution of regression problems in order to predict time series. In this paper, the problem of linear and non-linear regression is developed for the prediction of a time series using Vector Support Machines (VSM), in order to show the advantages obtained with conventional regression techniques. For this, a UCI Machine Learning database was taken consisting of the variation of 8 design parameters for the energy efficiency of one. 4718 Pedro Pablo Cárdenas Alzate et al.
Design And Evaluation Of A Mobile User Interface Usability

This research has intended to identify the importance of the usability factor in the creation of a mobile application. Basically, when it comes to directory information, most of the tourists use a conventional method, such as printed maps, traveling books, online or traveling websites and also travel agents. From my perspective and with support from the field research, language impediments and directory issues have been the most common problems in this research. While Smartphone’s and apps are, increasingly, being used nowadays, there are not sufficient studies addressing the usability of smartphone user interfaces or applications that are focused for tourist guides. This paper describes the design and evaluation process of the user interface of a smartphone application designed to be a guide or directory for tourists. Two successive versions of the user interfaces were tested with different groups. The results and findings from two rounds of usability tests led to recommendations regarding an inclusive design and the designing of apps that are useful for tourists and which may be a useful contribution to the broader community when designing interfaces for smartphones. Overall, the users enjoy using the new application that is more user friendly and easier to use and navigate with. The findings can be used as a reference to set certain standards in mobile application design and creation, and also to be used for academic benefits.
Impacts of Tropical Cyclones in the Northern Atlantic on Adverse Phenomena Formation in Northeastern Brazil

Tropical cyclone (TC) impacts on adverse phenomena in the tropical region of Northeastern Brazil (NEB) have been analyzed. TC influence on fog and rain formation was not described in the previous papers. The main goal of the chapter is to evaluate the existence of such influence and thus to improve the weather forecasting in this area. TC information from the NHC of the NOAA was used. METAR and SYNOP data were used for the adverse phenomena study. Analysis of the synoptic systems was based on different maps at the pattern levels and on satellite images. These maps were elaborated using reanalysis data from the ECMWF. Thermodynamic analysis was also used. Middle tropospheric cyclonic vortexes (MTCV) in the tropical region of the Southern Atlantic were described recently. Five from 10 MTCVs were associated with tropical cyclones and disturbances in the Northern Atlantic. Circulation patterns between TC and synoptic systems at the NEB are described. These circulations create sinking over the BNE and, as a result, form fog, mist and weak rain in the BNE during TC days. Mechanisms of TC influence on weather formation in the BNE are presented. This information is important for improving weather forecasting methods.
Landslide Disaster in Malaysia: An Overview

In recent times growing population and accelerative economic condition have led to the construction of high-rise condominiums and expansion of settlements and lifelines over the hilly areas in Malaysia. Due to these development activities risk of landslide disaster events with potential of causalities and economic damage greater than before is increasing. Under such circumstances, number of research efforts conducted in Malaysia has been quickly increasing in recent year, which indicates that landslide is now being considered not only as natural events or a result of design fault, but as a greater risk for the society that needs to be managed in a scientific and systematic way rather than in a haphazard way. The focus of this review is to define knowledge gaps between the current research outcomes and the future research necessities, which are highly recommended to be focused on in order to establish a sustainable society with rapid development and urbanization in Malaysia. From the review it can be concluded that a lot of works have been done so far on model development, mapping and risk zonation but a limited number of researches has been carried out on the causal factor’s analysis, sensitivity analysis and socioeconomic characterization. Even few studies have been conceded on response and behavioral aspects of the societies and the crisis management in the events of landslide. It should also be pointed out that, most of the research has been focusing on the, peninsular Malaysia, but not on Sabah and Sarawak in Borneo Malaysia. The reviewers propose to establish an integrated data base on landslides occurred in both Peninsular and Borneo Malaysia. A sound collaborative linkage-based research guideline among the researchers’ the policy makers and the residents must be established for better understanding of the facts and figures of Malaysian landslide disaster and its risk.
Quantitative Phenotyping of Northern Leaf Blight in UAV Images Using Deep Learning

Plant disease poses a serious threat to global food security. Accurate, high-throughput methods of quantifying disease are needed by breeders to better develop resistant plant varieties and by researchers to better understand the mechanisms of plant resistance and pathogen virulence. Northern leaf blight (NLB) is a serious disease affecting maize and is responsible for significant yield losses. A Mask R-CNN model was trained to segment NLB disease lesions in unmanned aerial vehicle (UAV) images. The trained model was able to accurately detect and segment individual lesions in a hold-out test set. The mean intersect over union (IOU) between the ground truth and predicted lesions was 0.73, with an average precision of 0.96 at an IOU threshold of 0.50. Over a range of IOU thresholds (0.50 to 0.95), the average precision was 0.61. This work demonstrates the potential for combining UAV technology with a deep learning-based approach for instance segmentation to provide accurate, high-throughput quantitative measures of plant disease.
Review of the Classification of Massive Chinese Texts Based on Spark

As the Internet develops rapidly, the number of texts is also growing rapidly. Whether it is the content of online emails exchanged by people, or the online novels and other literary contents, or news reports, personal blogs, Weibo or comments, they are constantly increasing the amount of text at all times. However, most of the data is not classified or processed, which causes a lot of spam, junk information, meaningless articles or advertisements. Their production not only consumes a lot of Internet resources, but also affects users' online experience and reduces the users' work and study efficiency. Therefore, it is vital accurately classify a large amount of text, judge its nature according to the classification result, and carry out targeted treatment. The classification of massive texts based on Spark framework is reviewed in this paper.
Determine point-to-point networking interactions using regular expressions

point-to-point using regular more the number of concurrent data flows start to increasing, makes in and corporate ability to identify point-to-point interactions. The best is this paper. This paper represents the principles of building system, which searches for a regular expression match using computing on graphics adapter in server station. A significant computing power and capabil-ity to parallel execution on modern graphic processor allows inspection of large amounts of data through sets of rules. Using the specified characteristics can lead to increased computing power in 30…40 times compared to the same setups on the central processing unit. The potential increase in bandwidth capacity could be used in systems that provide packet fire-walls and network
Indoor air pollution of PM2.5 in urban households of Jammu, (J&K)

The rising problem of Respirable Particulate Matter i.e. PM2.5 and smaller is catching attention of the policymakers, stakeholders as well as common man. The study of the IndoorPM2.5 of the particular area is very important as it is having direct impact on the human health because PM2.5is absorbed into lung alveolar tissues during breathing and causes respiratory and cardiovascular problems. In present study attempt has been made to assess the status of Indoor PM2.5 in Urban Households of Jammu, (J&K). The average indoor PM2.5 in all the sampled households of Jammu was observed to be 99.49±35.84 µg/m3 which is above the permissible limits of PM 2.5 as prescribed by CPCB. This type of study has been done for the first time in the northern region of India. The data generated in present study will act as base line data for further studies pertaining to its ionic analysis as well as suggesting mitigation measures
MAPEAMENTO DO USO E COBERTURA DO SOLO DE MOÇAMBIQUE UTILIZANDO A PLATAFORMA GOOGLE EARTH ENGINE

In Brazil, the Cerrado biome, the second largest in our territory, has a well-established agricultural occupation. In the African continent, another savanna area deserves attention, the Mozambican miombo, which although quite fragmented is in a lower state of anthropization compared to the Cerrado. The objective of this study was to map the Mozambique Use Cover and Land Cover (UCLC) using the Google Earth Engine (GEE) Platform, which proved to be an important tool for exploring a high data range. For Mozambique this mapping was performed using images from the Landsat-8 and Sentinel-2 satellites, which presented a global agreement of 76.23% among the classes of use mapped. The cover of remnants of native vegetation of the Mozambican miombo had an average value of 62.25% of its preserved area.
Automatic Initialization for 3D Ultrasound CT Registration During Liver Tumor Ablations

Ablation is a medical procedure to treat liver cancer where a needle-like catheter has to be inserted into a tumor, which will then be heated or frozen to destroy the tumor tissue. To guide the catheter, Ultrasound(US) imaging is used which shows the catheter position in real time. However, some tumors are not visible on US images. To make these tumors visible, image fusion can be used between the inter-operative US image and a pre-operative contrast enhanced CT(CECT) scan, on which the tumors are visible. Several methods exist for tracking the motions of the US transducer relative to the CECT scan, but they all require a manual initialization or external tracking hardware to align the coordinate systems of both scans. In this thesis we present a technique for finding an initialization using only the image data. To achieve this, deep learning is used to segment liver vessels and the boundary of the liver in 3D US images. To find the rigid transformation parameters, the SaDE evolutionary algorithm was used to optimize the alignment between the blood vessels and the liver boundary between both scans.
Effects of Memory Biases on Variability of Temperature Reconstructions

Quantifying past climate variation and attributing its causes improves our understanding of the natural variability of the climate system. Tree-ring-based proxies have provided skillful and highly resolved reconstructions of temperature and hydroclimate of the last millennium. However, like all proxies, they are subject to uncertainties arising from varying data quality, coverage, and reconstruction methodology. Previous studies have suggested that biological-based memory processes could cause spectral biases in climate reconstructions. This study determines the effects of such biases on reconstructed temperature variability and the resultant implications for detection and attribution studies. We find that introducing persistent memory, reflecting the spectral properties of tree-ring data, can change the variability of pseudoproxy reconstructions compared to the surrogate climate and resolve certain model–proxy discrepancies. This is especially the case for proxies based on ring-width data. Such memory inflates the difference between the Medieval Climate Anomaly and the Little Ice Age and suppresses and extends the cooling in response to volcanic eruptions. When accounting for memory effects, climate model data can reproduce long-term cooling after volcanic eruptions, as seen in proxy reconstructions. Results of detection and attribution studies show that signals in reconstructions as well as residual unforced variability are consistent with those in climate models when the model fingerprints are adjusted to reflect autoregressive memory as found in tree rings.