Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactions between agroecosystems and rural communities

Introduction, C.B. Flora Shifting Agroecosystems and Communities, C.B. Flora Altered Landscapes and Transformed Livelihoods: Banana Companies, Panama Disease, and Rural Communities on the North Coast of Honduras, J. Soluri Community Culture and the Evolution of Hog Production: Eastern and Western Oklahoma, C. Mayda Forest Conservation and Degradation in a Subsubsistence Agricultural System: Community and Forestry in Mexico, D. Klooster Community, Fruits, and Vegetables for Export: The Impact on Two Mexican Ecosystems and Rural Communities, M.B. Nock Communities of Interest and Agroecosystem Restoration: Streuobst in Europe, F. Herzog and A. Oetmann Transhumant Communities and Agroecosystems in Patagonia, M. Bendini Farm-Community Entrepreneurial Partnerships in the Midwest, C.B. Flora, G. McIsaac, S. Gasteyer, and M. Kroma A Learning Approach to Community Agroecosystem Management, C. Lightfoot, M. Fernandez, R. Noble, R. Ramirez, A. Groot, E. Fernandez-Baca, F. Shao, G. Muro, S. Okelabo, A. Mugenyi, I. Bekalo, A. Rianga, and L. Obare Bridges to Sustainability: Links Between Agriculture, Community, and the Ecosystem, L.M. Butler and R. Carkner Rural Community Leadership in the Lake Benton Watershed, W. Monson The Winnebago Tribe's Agroforestry Project: Linking Indigenous Knowledge, Resource Management Planning, and Community Development, L.C. Rule, M.B. Szymanski, and J.P. Colletti Innovation in Indigenous Production Systems to Maintain Tradition, M. de Lourdes Baron and D. Barkin Ethnicity, Multiple Communities, and the Promotion of Conservation: Strawberries in California, D.C. Mountjoy Ecobelts: Reconnecting Agriculture and Communities, M.M. Schoenberger, G. Bentrup, and C. A. Francis Afterward: An Optimistic Future Scenario, C.A. Francis Index
Sun-Moon gravitation-induced wave characteristics and climate variation

[1] Understanding periods associated with climate variations has been challenging and has attracted scientific study. In the work presented here, we establish a theoretical dynamical model driven by Sun-Moon gravitation (SMG) and present basic SMG wave characteristics and SMG-induced nonlinear motions for geophysical fluids. As compared to observations, waves and motions demonstrate climate variations associated with abundant structures and climatic rhythms, including the 30–60 day oscillation, seasonality, El Nino–Southern Oscillation–like interannual variation, etc. In our work, periods depended upon the obliquity and revolution velocity of the Sun and Moon; the speed of geophysical fluids; and the latitude, radius, and rotation velocity of Earth. The rotation of Earth helps fluids remember and accumulate momentum in geophysical fluids that are provided by the SMG on multiple time scales, which may contribute to multiperiods of climate oscillations. The speed-dependent periods of SMG-induced flow are of a broad spectrum (i.e., faster speeds, shorter periods). SMG-induced flow in an atmosphere of faster flow tends to have shorter (e.g., seasonal and annual) periods, while an ocean of slower flow tends to have longer (e.g., annual and interannual) periods.
Automatic Assessment System Using Topic Modelling and TF-IDF Approach

Topic modelling has changed the way to do text mining. It is a technique to discover topics and make clusters of similar words in large volume of documents. After analyzing almost 3000 medium articles on topic modeling, an extensive survey on topic modelling has been presented in this paper. It includes Topic modelling methods, different evolution models of latent Dirichlet allocation (LDA) and its utilization in different areas of technology. The LDA operate and assess documents in the form of multinomial distribution. Similarly, every topic is assessed in the form of multinomial distribution over words. LDA can calculate and analyze the steadily increasing words in a particular corpus and can be utilized as a good resemblance of natural text. Essays are most useful ways for checking knowledge, but manual grading might miss out on some minor details and lead to errors in result generation. Therefore, we believe that automatic assessment system is an optimal solution to tackle this issue. We propose using Topic Modelling usage for the assessment system. Our research paper is an attempt to investigate whether automatic assessment systems can detect similar information without guessing meaning of sentences based on in structurally different texts, the way examiner does without guessing meaning of sentences based on word or need to classify entire document based on topic before evaluation. Earlier research on these methods show that machine matches four out of five human findings which also gives room for improvement.
Nonlinear dictionary learning algorithm with nonconvex regularizations

Nonlinear dictionary learning can process and model nonlinear signals more accurately than mainstream dictionary learning methods. However, existing nonlinear dictionary learning is based on convex sparse regularization, which is difficult to achieve the desired results. In this paper, we propose a nonlinear dictionary learning algorithm based on DCA direct optimization using the minimax-concave penalty (MCP) and the generalized mini- max-concave (GMC) sparse regularization, which is nonconvex, to enforce the strong sparsity of the model and to obtain the exact solution. We compare the proposed algorithms with the corresponding linear dictionary learning algorithms in numerical simulations and real image denoising experiments. The experimental results demonstrate the effectiveness of our algorithms.
Book Review: Ecotourism and Sustainable Development: Who Owns Paradise?

The concept of ecotourism - in search of the golden toad the world travel industry - going green? ecotourism today national studies - the Galapagos - paradise lost Costa Rica - on the beaten path Cuba - growth of tourism and ecotourism during the "special period" Tanzania - whose Eden is it? Zanzibar - ecotourism on a Muslim Island Kenya - the maze of ecotourism in Africa South Africa.
Word embeddings for protein sequence analysis

Nowadays, the ability to predict protein functions directly from amino acid sequences alone remains a major biological challenge. The understanding of protein properties and functions is extremely important and can have a wide range of biotechnological and medical applications. High-level representations from the field of deep learning can provide new alternatives to address these problems, particularly Natural Language Processes methods, such as word embeddings (WE), which have shown particular success when applied to protein sequence analysis. Here, a software tool that eases the implementation of WE models toward protein representation and classification is presented. This tool was validated using two protein classification problems namely, the identification of plant ubiquitylation sites and lysine crotonylation sites, and further used to explore enzyme functional annotation. Several WE were tested and fed to different Machine and Deep Learning networks. Overall, WE achieved good results being even competitive with state-of-the-art, reinforcing the idea that language-based methods can be applied with success to a wide range of protein classification problems.
DTMCA: A Digital Twin Model for Stripe Rust Based on Cellular Automata

This paper presents a dynamic reasoning method of wheat stripe rust based on Cellular automaton. This method improves the characteristic that the basic Cellular automaton can only spread in a certain distance neighborhood. This article adjusts the circular field according to the size of plaque at the stage of wheat stripe rust infection (after symptoms) and their impact on the spread distance of stripe rust. This method optimizes the problem of fixed transmission range in previous studies, and based on this, uses attenuation formulas to prevent repeated infection of the leaves in the block, and displays the transmission path of stripe rust at the level of farmland. This provides a reference mechanism model for the digital twin of stripe rust.
No Forking Way: Detecting Cloning Attacks on Intel SGX Applications

Forking attacks against TEEs like Intel SGX can be carried out either by rolling back the application to a previous state, or by cloning the application and by partitioning its inputs across the cloned instances. Current solutions to forking attacks require Trusted Third Parties (TTP) that are hard to find in real-world deployments. In the absence of a TTP, many TEE applications rely on monotonic counters to mitigate forking attacks based on rollbacks; however, they have no protection mechanism against forking attack based on cloning. In this paper, we analyze 72 SGX applications and show that approximately 20% of those are vulnerable to forking attacks based on cloning—including those that rely on monotonic counters. To address this problem, we present CloneBuster, the first practical clone-detection mechanism for Intel SGX that does not rely on a TTP and, as such, can be used directly to protect existing applications. CloneBuster allows enclaves to (self-) detect whether another enclave with the same binary is running on the same platform. To do so, CloneBuster relies on a cache-based covert channel for enclaves to signal their presence to (and detect the presence of) clones on the same machine. We show that CloneBuster is robust despite a malicious OS, only incurs a marginal impact on the application performance, and adds approximately 800 LoC to the TCB. When used in conjunction with monotonic counters, CloneBuster allows applications to benefit from a comprehensive protection against forking attacks.
GETAvatar: Generative Textured Meshes for Animatable Human Avatars

We study the problem of 3D-aware full-body human generation, aiming at creating animatable human avatars with high-quality textures and geometries. Generally, two challenges remain in this field: i) existing methods struggle to generate geometries with rich realistic details such as the wrinkles of garments; ii) they typically utilize volumetric radiance fields and neural renderers in the synthesis process, making high-resolution rendering non-trivial. To overcome these problems, we propose GETAvatar, a Generative model that directly generates Explicit Textured 3D meshes for animatable human Avatar, with photorealistic appearance and fine geometric details. Specifically, we first design an articulated 3D human representation with explicit surface modeling, and enrich the generated humans with realistic surface details by learning from the 2D normal maps of 3D scan data. Second, with the explicit mesh representation, we can use a rasterization-based renderer to perform surface rendering, allowing us to achieve high-resolution image generation efficiently. Extensive experiments demonstrate that GETAvatar achieves state-of-the-art performance on 3D-aware human generation both in appearance and geometry quality. Notably, GETAvatar can generate images at 5122 resolution with 17FPS and 10242 resolution with 14FPS, improving upon previous methods by 2×. Our code and models will be at https://getavatar.github. io/.
Single-stage single-switch curved air gap power factor correction integrated flyback transformer design for lighting equipment power applications

The paper presents a design of a single-stage single switch flyback transformer, which incorporates two auxiliary windings and a curved air gap. The main objective of this design is to enhance transformer efficiency and reduce harmonic current. To validate the proposed design, a 250W prototype circuit was constructed, simulations and experiments were conducted using four ferrite materials. The results obtained from both FEM simulations and experiments are promising, indicating the effectiveness of the design. The proposed transformer configuration demonstrated improved efficiency and a reduction in harmonic current.
Monitoring and Evaluation of Water Availability of the South of Ukraine and Russian Federation with Usage of the Standardized Precipitation Index

Abstract To obtain integrated indicators of water availability of the – The methodology of the Standardized Precipitation Index (SPI) usage for evaluation of the level of water availability of the territory for the estimated period in comparison with long-term precipitation rate is given in this paper. Using the methodology of normalized parameters assessment gives possibility to make it comparable for different territories and regions as well as for different time scale, enable to conduct a retrospective analysis, evaluate the current situation or study the influence of probable climate change scenarios. Examples of water availability evaluation mapping of the South of Ukraine and Russia by SPI on the base of processing of the long-term precipitation records and weather data of spring 2014 with GIS tools using are given. Recommendations on the Standardized Precipitation Index application for the evaluation of agricultural and hydrological droughts and potential risk for waterworks objects have been proposed.
Tsunamis - Assessing the hazard for the UK and Irish coast

Following completion of the 2005 Defra commissioned study “The threat posed by tsunamis to the UK”, this study was undertaken to investigate more specific questions raised from the previous report. The original Defra study identifies four potential tsunami sources origins, and provided first estimates for wave conditions at the UK coast for tsunamigenic events of very high, high and moderate likelihood. This second study reviewed two of these source origins in more depth, the North Sea event and a Lisbon-type event, with their consequence impact compared with regard to hazard. Previously proposed source terms for a 1755 Lisbon event was assessed and three simple models considered that could be used to study the impact of a tsunamigenic earthquake of a similar size, and in a similar region to the 1755 source, on the UK and Irish coastline. The resulting sea level displacements were used as initial conditions in a numerical model to propagate the initial disturbance to nearshore. A further numerical model propagated the tsunami to the shoreline and provided estimated of water level elevations on the Southern Irish coast, the Cornish coast and in the Bristol Channel. Information regarding the tsunami magnitude at the coast was then used to assess hazard. This paper focuses on one of the hypothesised Lisbon type events, the propagation of the tsunami from source to shoreline and the consequence of an impact on the coastlines of south-west England and southern Ireland.
TCSE_BiLSTM: Spatial-Temporal Characteristics Extraction Using Deep Learning to Improve Tropical Cyclone Size Estimation from Infrared Satellite Imagery

Currently, size feature extraction for tropical cyclones (TCs) from satellite data is largely based on subjective human experience and archived satellite data. There are few objective methodologies for estimating the size of a TC. To overcome this, in this paper, we introduce a novel deep learning model, which we call TCSE_BiLSTM. The model is designed to fully extract the spatial-temporal characteristics of TC size from infrared satellite images using the current and previous three intervals. To verify the model’s performance, we conducted experiments on TC wind radii estimation using the TCSE_BiLSTM model on infrared satellite images of the Northwest Pacific region. Our experiments showed that the proposed deep spatial-temporal feature extraction network has advantages in estimating TC wind radii over current methods. Therefore, it can be used for fully automated TC wind radii estimation.
A Survey on Various Image Inpainting Techniques A Survey on Various Image Inpainting Techniques

Over the decades' researchers have studied the image inpainting problem intensively due to its high significance and effectiveness in various image processing applications such as people and object security, object removal, face editing applications. Image inpainting is defined as the process of completing or removing a missing region in images. It is considered one of the most challenging topics in the image processing field, although, it requires a deep understanding of the image details in terms of texture and structure. In this paper, a survey of most image inpainting techniques is presented and summarized with comparisons including the merits and demerits of each technique which could help researchers in evaluating their proposed techniques against.
Diffusion-weighted MR imaging: role in the differential diagnosis of breast lesions.

PURPOSE To evaluate the diagnostic value of magnetic resonance diffusion-weighted imaging (DWI) using apparent diffusion coefficient (ADC) values to the characterization of breast lesions and differentiation of benign and malignant lesions. MATERIALS AND METHODS Thirty-seven women (mean age, 38 years) with 37 enrolled in the study. DWI and ADC maps in the axial plane were obtained using a 1.5 Tesla MRI device. Mean ADC measurements were calculated among cysts, normal fibroglandular tissue, benign lesions and malignant lesions were evaluated. RESULTS Out of 37 women, 4 had normally breast MRI findings. The diagnosis of remaining 33 patients with 37 breast lesions were as follows; malign lesions (n = 23), benign lesions (n = 10) and simple breast cyst (n = 4). The ADC values were as follows (in units of 10(-3) mm2/s): Normal fibroglandular tissue (range: 1.39-2.06; mean: 1.61 ± 0.23), benign breast lesions (range: 1.09-1.76; mean: 1.47 ± 0.25), cyts (range: 2.27-2.46, mean: 2.37 ± 0.07) and malignant breast lesions (range: 0.78-1.26, mean: 0.96 ± 0.25). The mean ADC obtained from malignant breast lesions was statistically different from that observed in benign solid lesions (p < < 0.01) and normal fibroglandular breast tissue (p < 0.01). Furthermore, the mean ADC values of benign breast lesions was not statistically different from cyst (p ≥ 0.01) and normal fibroglandular breast tissue (p ≥ 0.01). A ADC value of 1.1 x 10(-3) mm'/s as a treshold value provided differantiation for malign and benign lesions, with a sensitivity of 91.3% and a specificity of 85.7% compared with conventional breast MRI values. CONCLUSION DWI with quantitative ADC measurements is a reliable tool for differentiation of benign and malignant breast lesions.
Two Ultrahigh-Pressure Metamorphic Events Recognized in the Central Orogenic Belt of China: Evidence from the U-Pb Dating of Coesite-Bearing Zircons

A ~4000 km long ultrahigh-pressure metamorphic (UHPM) belt in northern China has been documented on the basis of the discovery of coesite-bearing rocks in the Altun-North Qaidam terrane in the western Central Orogenic Belt (COB), and diamond-bearing rocks in Qinling in the central and Dabie-Sulu terrane in the east. New SIMS and SHRIMP U-Pb dates of zircons from coesitebearing UHPM rocks indicate two UHPM events: one in the early Paleozoic and the other in the Triassic. Coesite-bearing zircons from a North Qaidam gneiss yielded UHP metamorphic ages of 452 ± 13.8 Ma and retrograde ages of 419 ± 6.7 Ma. A diamond-bearing gneiss from Qinling gave a lower intercept age of 502 ± 45 Ma, and an upper intercept age of 1545 ± 100 Ma, whereas a Qinling eclogite sample gave a lower intercept age of 493 ± 170 Ma and an upper intercept age of 1381 ± 82 Ma. The lower and upper intercept ages of the Qinling samples are interpreted as UHPM and protolith ages of the rocks, respectively. Coesite-bearing zircons from a Qinglongshan eclogite in the south Sulu belt yielded early Paleozoic UHPM ages of 441 ± 9 Ma, 449 ± 9 Ma, and 442 ± 9 Ma, whereas the core of a zircon containing plagioclase and apatite inclusions gave a protolith age of 761 ± 13 Ma. These age data suggest that the early Paleozoic UHPM rocks extend from west to east for about 4000 km across the COB, whereas the Triassic UHPM belt extends across the Dabie-Sulu region for about 1000 km. Based on available geochronological and geochemical data, we suggest the following tectonic model for evolution of the COB. At about 1000 Ma, the area was amalgamated to form the Rodinian continent, which contained ophiolitic fragments of oceanic affinity. This part of Rodinia was then rifted at about 800-750 Ma to form an oceanic basin with a variety of MORB and intruded by granitic plutons. Closure of this ocean basin produced Neoproterozoic ophiolites and granitic gneisses. The UHPM rocks, along with subduction-related island-arc volcanics and granites of early Paleozoic age suggest a second cycle of rifting and subduction along the COB, whereas the Triassic UHPM rocks record a final subduction and collision event between the North China and South China blocks.
Trascolación y escorrentía cortical en la cuenca experimental de San Salvador, Pirineo Central español

Throughfall and stemflow have been studied in a forest-covered catchment in the Central Spanish Pyrenees. The San Salvador catchment (0,92 km2) is located in the Aisa Valley, in which trends in plant cover evolution show an increase of the presence of open and dense forests, after the abandonment of agricultural activities since the middle of the 20th Century. San Salvador catchment shows a dense forest in all area (more than 90%). Pinus sylvestris, Fagus sylvatica and Quercus gr. faginea, forest patches alternate in the catchment according to altitude and shape of the slopes (concave, convex). Three open plots have been selected in the San Salvador catchment, corresponding to the three types of forest cover. The results (April 2006-April 2008) has demonstrated that the percentages of throughfall are associated with type of forest cover, due to differences in the morphology of the leaves and the foliage density. Thus, the species that causes a major interception is Fagus sylvatica, while Quercus gr. faginea and Pinus sylvestris has shown a similar enough seasonal behaviour, the last one more homogenous due to the invariable coverage.
Three Dimensional Beach-Stage Model

A three dimensional beach model applicable to open sandy coastal environments is presented. The model consists of ten beach stages incorporating erosional and accretionary sequences of beach-surfzone morphody-namic conditions. Each stage is associated with a particular level of breaker wave power. Decreasing breaker wave power produces spatially controlled onshore bar migration, eventual bar welding, beach accretion and reflective surfzone conditions ($$beach stages 6 \rightarrow 5 \rightarrow 4 \rightarrow 3 \rightarrow 2 \rightarrow 1$$). Increasing wave power generates beach erosion, dynamically controlled bar-channel formation and dissipative surfzone conditions (stages $$1 \rightarrow 2 \rightarrow 3 \rightarrow 4 \rightarrow 5 \rightarrow 6$$). Temporal variations in wave power cause predictable movement through and within the model. The effect of beach gradient (tan $$tan \beta$$) is considered with regard to the influence on the degree of dissipativeness, edge wave length and cut-off modes, and standing wave length. Steeper coarse grained beaches are more reflective and tend to lower (1, 2, 2') reflective stages; fine sand, low gradient dissipative beaches favor outer and multiple bars reflecting higher stages (5, 5' and 6); with low to moderate gradient, medium sand beaches potentially encompassing the entire spectrum of beach stages presented in the model.
Two new species of

The order Albuginales contains the causal agents of white blister rust disease and currently comprises the three genera Albugo, Pustula, and Wilsoniana. Following surveys conducted during the growing seasons of 2018–2019, samples of white blister rust pathogens of the genus Pustula were taken from three asteraceous hosts including Senecio vernalis, S. vulgaris, and Xeranthemum inapertum in the northern Iranian provinces Golestan and Guilan. Based on morphological and molecular analyses, two new species, Pustula senecionis sp. nov. on Senecio spp. and Pustula thinesii sp. nov. on Xeranthemum inapertum, are introduced and illustrated. The latter species can be distinguished from P. spinulosa by its smaller oospores, and primary and secondary sporangia, and from P. centaurii by its smaller oospores and secondary sporangia.