Miracle-dz/UniFAR-FTUs huggingface dataset:
UAS-LC-GNSS: Precision Surveying with a Low-Cost GNSS System for Commercial Drones

INGV (National Institute of Geophysics and Volcanology, Italy) is one of the institutions that studies and monitors the geophysical phenomena (earthquakes, volcanic eruptions, landslides, etc.) that occur on Earth. During these events, it is essential to carry out a large, detailed and fast map of the affected areas. If we think of the difficulties encountered during the mapping of the fault sources for the 2016 earthquake in central Italy, we can understand how the UAS (Unmanned Aircraft System) can be a valid “low-cost” alternative to the traditional methods of surveys. These devices, thanks to precision instrumentation such as GNSS (Global Navigation Satellite Systems) receivers and IMU (Inertial Measurement Unit) control units, allow a detailed reconstruction of the investigated areas, especially for small-scale analysis applications. These aircraft are based on multiple technologies and show great investigative capabilities, therefore they must be considered as complete systems. Starting from these concepts, we have developed a low-cost RTK/PPK (Real Time Kinematic/Post Processing Kinematic) GNSS survey system on “commercial” UAVs (Unmanned Aerial Vehicles), i.e. professional drones that are not created to be modified. We have demonstrated how the integration of a GNSS RTK/PPK module on commercial UAVs makes the system efficient for the reconstruction of a highly detailed and precise DEM (Digital Elevation Model), without using GCP (Ground Control Point), allowing to make precision measurements in areas that are difficult to explore and investigate. Indeed, the altimetric trends of the PPK processing without GCPs are perfectly comparable with those of the PVs (Verification Points) deriving from RTK analysis and sshow small acceptable deviations. The height differences between PVs measurements and those deriving from the DEM in the same planar coordinates vary between a minimum of 1 cm and a maximum of 7.8 cm. Based on these results, we can state that the precision mapping with a drone equipped with an on-board GNSS module does not differ much from the technique that involves measuring GCP on the ground, in reality, it is comparable in terms of errors, even on the more difficult field of altitudes.
Vaginal Microbiome Dynamics of Cows in Different Parities

Simple Summary At present, research on the vaginal microbiome of dairy cows is mostly cross-sectional, and there is still room for research on the relationship between the vaginal microbiome and cow reproductive age. In this study, high-throughput 16S rRNA sequencing technology was used to explore vaginal microbiota differences in dairy cows of different parities and thus gain an in-depth understanding of cow reproductive physiology. Studies have found that vaginal microorganisms in cows change significantly before and after the first calving, and the importance of the first production of cows to the establishment and reproduction of subsequent vaginal microorganisms may be more important than previously thought. There was no significant change in the vaginal microbiota of calves in subsequent production, and the number of vaginal microorganisms gradually decreased with the increase in parity, but the vaginal microbiota tended to be stable. The specific mechanism of vaginal microbiome changes in dairy cows needs further study. Abstract At present, there is still room for research on the relationship between the vaginal microbiome and the reproductive health of dairy cows. In this study, high-throughput 16S rRNA sequencing technology was used to explore the differences of bacterial communities of dairy cows of different births, gain a deeper understanding of cow reproductive physiology, and maintain cow health. With the increase in parity, the number of vaginal flora decreased from 3511 to 469, but the number of species increased significantly, and Chao1 increased from 1226.41 ± 345.40 to 1467.76 ± 269.76. There was a significant difference in the number of vaginal microbiome functions between uncounted cows and calving cows. There was no significant difference in microbial diversity in calves. The relative abundance variation of vaginal microbiota in high-parity cows is less than that in low-parity cows. The amino acid metabolism of calves increased, the endocrine function of high-parity cows was enhanced, and the function of the vaginal microbiome increased after the first delivery, which gradually decreased with the increase in parity. This study also found that Methanobacteria and Caviibacter may be involved in amino acid metabolism and endocrine function, and they may play a key role in cow reproduction. This study provides an important theoretical basis for studying changes in vaginal microorganisms in dairy cows, improves the understanding of reproductive health and production performance, and provides a scientific basis for improving the reproductive management of dairy cows.
RESSCAL3D: Resolution Scalable 3D Semantic Segmentation of Point Clouds

While deep learning-based methods have demonstrated outstanding results in numerous domains, some important functionalities are missing. Resolution scalability is one of them. In this work, we introduce a novel architecture, dubbed RESSCAL3D, providing resolution-scalable 3D semantic segmentation of point clouds. In contrast to existing works, the proposed method does not require the whole point cloud to be available to start inference. Once a low-resolution version of the input point cloud is available, first semantic predictions can be generated in an extremely fast manner. This enables early decision-making in subsequent processing steps. As additional points become available, these are processed in parallel. To improve performance, features from previously computed scales are employed as prior knowledge at the current scale. Our experiments show that RESSCAL3D is 31-62% faster than the non-scalable baseline while keeping a limited impact on performance. To the best of our knowledge, the proposed method is the first to propose a resolution-scalable approach for 3D semantic segmentation of point clouds based on deep learning.
Mapping of vine vigor by UAV and anthocyanin content by a non-destructive fluorescence technique

Multispectral remote sensing using Unmanned Aerial Vehicles (UAV) is a promising new technique for precision viticulture because of its flexibility of use and limited cost. On the other hand, non-destructive methods to control vine vegetation status and ripening level of bunches are fundamental to produce high quality grape and top quality wines. Here, new techniques to evaluate the spatial distribution of vine vigor and phenolic maturity have been applied to the Nerello Mascalese Sicilian cultivar in the Etna region. Mapping of the normalized difference vegetation index (NDVI) was obtained by using a high-resolution multispectral camera mounted on an UAV. The spatial variability of grape anthocyanin content was detected in situ by using a fluorescence-based sensor. The two techniques appeared suitable to compare vine related information on a relatively large scale.
Understanding the Signal-to-noise Paradox in Decadal Climate Predictability from CMIP5 and an Eddy-resolving GCM

Recent research suggests the widespread existence of the signal-to-noise paradox in seasonal-to-decadal climate predictions. The essence of the paradox is that the signal-to-noise ratio in models can be unrealistically small and models may make better predictions of the observations than they predict themselves. The paradox highlights a potentially serious issue with model predictions as previous studies may underestimate the limit of predictability. The focus of this paper is two-fold: the first objective is to re-examine decadal predictability from the lens of the signal-to-noise paradox in the context of CMIP5 models. We demonstrate that decadal predictability is generally underestimated in CMIP5 models possibly due to the existence of the signal-to-noise paradox. Models underestimate decadal predictability in regions where it is likely for the paradox to exist. The second objective follows from the results of the first, attempting to determine if this underestimate of decadal predictability is, at least partially, due to missing ocean mesoscale processes and features in CMIP5 models. A suite of coupled model experiments is performed with eddy-resolving and eddy-parameterized ocean component. Compared with eddy-parameterized models, the paradox is less likely to exist in eddy-resolving models, particularly over eddy-rich regions. These also happen to be regions where increased decadal predictability is identified. We hypothesize that this enhanced predictability is due to the enhanced vertical connectivity in the ocean. The presence of mesoscale ocean features and associated vertical connectivity significantly influence decadal variability, predictability, and the signal-to-noise paradox.
Carbon Sequestration through Farm forestry: Case from India

Forests constitute both a sink and a source of atmospheric CO 2 , In developing countries like India, the potential land area available for the implementation of forest management options for carbon conservation and sequestration is constrained by socio-economic circumstances. Farm Forestry involves the growth and management of trees on private lands and this provides an excellent opportunity for carbon sequestration while supplying wood and non-wood products to meet both domestic and market requirements. Under the Farm Forestry programme in the State of Uttar Pradesh in India, nearly 1906.8 million trees have been planted during the period 1979-94 of 1525.44 million are estimated to be surviving. In terms of land coverage, this works out to over one million hectares. This is significant and adds up to nearly 30% of the entire good natural forest cover in U.P. State. It is estimated that nearly 20 million tonnes of Carbon has been sequestered by these Farm Forestry plantations. Government policies and programmes that are supportive of Farm Forestry, could be the major instruments for increasing carbon sequestration from Farm Forestry, thus contributing to the implementation of the Climate Change Policy.
Dynamics and organisation of precipitation bands in the midlatitudes.

Thesis title: Dynamics and organisation of precipitation bands in the midlatitudes.Submitted by Jesse Norris to The University of Manchester for the degree of Doctorof Philosophy (PhD). 24 March 2014.This thesis was funded by the Natural Environmental Research Council (NERC)as part of the Diabatic Influences on Mesoscale Structures in Extratropical Storms(DIAMET) project. The thesis is presented in alternative format, meaning that theresults of the thesis take the form of three journal articles, each telling a distinctstory within the subject matter, but collectively highlighting the sensitivity of bandsto frictional and diabatic processes.Paper 1 is an idealised-modelling study with the Weather Research and Fore-casting (WRF) model, in which moist baroclinic waves are simulated from an initialzonally uniform midlatitude jet on an f -plane at 20-km grid spacing, and the sen-sitivity of the resulting precipitation bands is explored. Paper 2 employs furtherWRF idealised-baroclinic-wave simulations and takes a simulation from Paper 1,after the cold front has formed, as the initial condition. A nested domain at 4-kmgrid spacing is inserted when this simulation is re-initialised to invesigate the sensi-tivity of finer-scale precipitation cores along the surface cold front. In both Papers 1and 2, friction and latent-heat release enhance multiple banding at the two distincthorizontal scales, while surface fluxes hinder multiple banding.Paper 3 studies postfrontal snowbands over the English Channel and Irish Seaduring extreme cold-air outbreaks in the winters of 2009? 10 and 2010? 11, via a cli-matology of precipitation-radar, sounding, and SST data, and real-data WRF sensi-tivity simulations of one such band over the English Channel. The observational andmodelling results show that strong winds and large differential heat fluxes betweenland and sea were necessary to generate banded precipitation. Coastal orographyand the land? sea frictional contrast aided the morphology of bands, but bandedprecipitation did still form in the absence of these influences in the sensitivity sim-ulations.These three studies and the thesis as a whole highlight the role of frictional anddiabatic processes in modifying various types of precipitation bands within baroclinicwaves, and in generating bands that would otherwise not exist.
High-dimensional instrumental variables regression and confidence sets -- v2/2012

This was a revision of arXiv:1105.2454v1 from 2012. It considers a variation on the STIV estimator where, instead of one conic constraint, there are as many conic constraints as moments (instruments) allowing to use more directly moderate deviations for self-normalized sums. The idea first appeared in formula (6.5) in arXiv:1105.2454v1 when some instruments can be endogenous. For reference and to avoid confusion with the STIV estimator, this estimator should be called C-STIV.
Fuel cells with lifting converters for alternative energies

espanolLa necesidad energetica en el mundo ha llevado a la busqueda de nuevas formas de generacion de energia electrica entre las que se encuentra el uso de celdas de combustible como fuente renovable que no contribuye a la contaminacion ambiental y tiene alta eficiencia en conversion energetica. En este tipo de tecnologias el sistema sufre fluctuaciones de tension debido a las cargas conectadas. Se utilizan convertidores elevadores de tension tipo boost, que permiten regular la tension a un valor optimo, sin grandes fluctuaciones. Se opto por el diseno del control tipo PI mediante el metodo de espacio de estados para obtener las funciones transferencia, y el criterio de Routh-Hurwitz para obtener las constantes del controlador PI. Se simulo un sistema para celda de combustible de 1 kW manteniendo constante la tension de salida del regulador a 48 V con una sobretension no mayor al 30% del valor deseado. EnglishThe need for energy in the world has led to the search for new ways of electric power generation, among which is the use of fuel cells as a renewable source that does not contribute to environmental pollution and has high efficiency in energy conversion. In this type of technology the system suffers voltage fluctuations due to the connected loads. Booster converters of boost type are used, which allow to regulate the tension to an optimal value, without great fluctuations. We chose the design of the PI type control by means of the state space method to obtain the transfer functions, and the Routh-Hurwitz criterion to obtain the constants of the PI controller. A fuel cell system of 1 kW was simulated keeping the regulator output voltage at 48 V constant with an overvoltage not greater than 30% of the desired value.
Vertical distribution of ice optical and microphysical properties in Arctic low-level mixed-phase clouds during ACLOUD

Low-level (cloud tops below 2 km) mixed-phase clouds are important in amplifying warming in the Arctic region through positive feedback in cloud fraction, water content and phase. In order to understand the cloud feedbacks in the Arctic region, good knowledge of the vertical distribution of the cloud water content, particle size and phase is required. Here we present seven in-situ vertical profiles of cloud microphysical and optical properties measured in the European Arctic during the ACLOUD campaign. Late spring-and summer-time stratiform clouds were sampled over pack ice, marginal sea ice zone and 5 open ocean surface with cloud top temperatures varying between -15 and -1.5 ◦ C. The results show that, although liquid phase dominates the upper parts of the clouds, ice phase was frequently observed in the lower parts down to cloud top temperatures as warm as -3.8 ◦ C. In the studied vertical cloud profiles the average liquid phase microphysical properties, droplet number concentration, effective radius and liquid water content, varied between 22 and 120 cm − 3 , 16 and 27 µ m , 0.09 and 0.48 gm − 3 , respectively. The average ice phase microphysical properties, ice number concentration, effective radius and ice water 10 content, varied between 0.01 and 35 L − 1 , 24 and 75 µ m , 0.003 and 0.08 gm − 3 , respectively. The elevated ice crystal number concentrations and ice water paths observed for clouds with cloud top temperatures between -3.8 and -8.7 ◦ C can be likely attributed to secondary ice production through rime-splintering. Low asymmetry parameters between 0.69 and 0.76 were measured for the mixed-phase ice crystals with a mean asymmetry parameter of 0.72. The effect of the ice phase for radiative transfer was investigated for the four cloud cases potentially affected by secondary ice production. Generally the ice phase has 15 only a minor effect to the cloud transmissivity and albedo, except in a case where ice phase dominated the upper cloud layer extinction. In this case cloud albedo was increased by 10%. The presented results highlight the importance of accurate vertical information of cloud phase for radiative transfer and provide a suitable data set for testing microphysical parameterisations in models.
Sustainable Tourism Destinations : A Pathway for Tour Operators

This paper examines the relationship between tour operators and their existing tourism destinations. The intent is to help the tour operators plan strategically for building the sustainability of their destinations. A Framework for Strategic Sustainability Development, based on scientific consensus, was used to structure this work. Interviews with tour operators and tourism experts gave practical insight complementing the literature review and case studies analysed during the research. The key findings were the need for tour operators to: consider a whole-systems perspective; cooperate with the tourism destination to build a common vision of success and a clear understanding of sustainability; and to prioritise their actions based on achieving the vision. From this the authors proposed guidance notes to assist tour operators in addressing these barriers. The paper concludes that tour operators can play a major role in building a sustainable society while perpetuating the tourism industry. In order to do so their actions must be chosen and managed correctly. This involves cooperation with the destinations throughout the strategic planning process and for all involved to be on the same page in terms of the end goal, a sustainable society.
Effect of Mixture Composed of Jeju' Scoria and Ecklonia cava on Anti-inflammation

The purpose of this study is to investigate the anti-inflammation effect of the mixture, consisting of a series of different ratio of Ecklonia cava extract and scoria. Also, to make more functional scoria powder into cosmetic material, studies on the toxicity by cell viability assay. Scoria is found in large amounts in Jeju Island, as an adsorbent of heavy metal ions (Ni 2 +, Zn 2 +, and Cr 3 +) in an aspect of its efficient utilization. Marine plants such as Ecklonia cava contain high amounts of polyphenolic antioxidants. The purpose of this study was to examine the anti-oxidative and anti-inflammation effects of combination of mixture of Eckloina cava extrat and scoria with optimal ratio. Therefore, this study suggested that combination of mixture of Eckloina cava extrat and scoria and its attenuated the oxidative and inflammatory reactions.
Deep Learning and Artificial Intelligence in Sustainability: A Review of SDGs, Renewable Energy, and Environmental Health

Artificial intelligence (AI) and deep learning (DL) have shown tremendous potential in driving sustainability across various sectors. This paper reviews recent advancements in AI and DL and explores their applications in achieving sustainable development goals (SDGs), renewable energy, environmental health, and smart building energy management. AI has the potential to contribute to 134 of the 169 targets across all SDGs, but the rapid development of these technologies necessitates comprehensive regulatory oversight to ensure transparency, safety, and ethical standards. In the renewable energy sector, AI and DL have been effectively utilized in optimizing energy management, fault detection, and power grid stability. They have also demonstrated promise in enhancing waste management and predictive analysis in photovoltaic power plants. In the field of environmental health, the integration of AI and DL has facilitated the analysis of complex spatial data, improving exposure modeling and disease prediction. However, challenges such as the explainability and transparency of AI and DL models, the scalability and high dimensionality of data, the integration with next-generation wireless networks, and ethics and privacy concerns need to be addressed. Future research should focus on enhancing the explainability and transparency of AI and DL models, developing scalable algorithms for processing large datasets, exploring the integration of AI with next-generation wireless networks, and addressing ethical and privacy considerations. Additionally, improving the energy efficiency of AI and DL models is crucial to ensure the sustainable use of these technologies. By addressing these challenges and fostering responsible and innovative use, AI and DL can significantly contribute to a more sustainable future.
ℋ∞ couple-group consensus of stochastic multi-agent systems with fixed and Markovian switching communication topologies

The paper addresses the issue of ℋ∞ couple-group consensus for a class of discrete-time stochastic multi-agent systems via output-feedback control. Both fixed and Markovian switching communication topologies are considered. By employing linear transformations, the closed-loop systems are converted into reduced-order systems and the ℋ∞ couple-group consensus issue under consideration is changed into a stochastic ℋ∞ control problem. New conditions for the mean-square asymptotic stability and ℋ∞ performance of the reduced-order systems are proposed. On the basis of these conditions, constructive approaches for the design of the output-feedback control protocols are developed for the fixed communication topology and the Markovian switching communication topologies, respectively. Finally, two numerical examples are given to illustrate the applicability of the present design approaches.
Ocean Acoustic Tomography: Single Slice and Moving Ship Experiments

Abstract : The results of the ocean acoustic tomography work that supported the development of matched field processing (MFP) are summarized. This report focuses on two experiments. In Slice89 a single source transmitted to a vertical hydrophone array. This experiment improved our understanding of the single slice transfer function from scales of internal waves to 1000 km. It demonstrated the importance of unresolved high wavenumber ocean mesoscale variability to acoustic propagation. Any coherent signal processing technique must be robust against both internal wave variability and unresolved high wavenumber mesoscale variability, as both contribute roughly comparable amounts of travel time variance. The Acoustic Mid-Ocean Dynamics Experiment - Moving Ship Tomography Experiment (AMODE-MST) was a large mapping effort to address the primary goal of this tomography effort-to determine the precision with which the ocean mesoscale sound speed field can be measured for input into matched field (or other) processing of long-range acoustic transmissions. The experiment demonstrated that tomographic techniques can be used to measure the sound speed structure over a large area with high resolution.