Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling Antarctic ice shelf basal melt patterns using the one-layer Antarctic model for dynamical downscaling of ice–ocean exchanges (LADDIE v1.0)

Abstract. A major source of uncertainty in future sea level projections is the ocean-driven basal melt of Antarctic ice shelves. While ice sheet models require a kilometre-scale resolution to realistically resolve ice shelf stability and grounding line migration, global or regional 3D ocean models are computationally too expensive to produce basal melt forcing fields at this resolution on long timescales. To bridge this resolution gap, we introduce the 2D numerical model LADDIE (one-layer Antarctic model for dynamical downscaling of ice–ocean exchanges), which allows for the computationally efficient modelling of detailed basal melt fields. The model is open source and can be applied easily to different geometries or different ocean forcings. The aim of this study is threefold: to introduce the model to the community, to demonstrate its application and performance in two use cases, and to describe and interpret new basal melt patterns simulated by this model. The two use cases are the small Crosson–Dotson Ice Shelf in the warm Amundsen Sea region and the large Filchner–Ronne Ice Shelf in the cold Weddell Sea. At ice-shelf-wide scales, LADDIE reproduces observed patterns of basal melting and freezing in warm and cold environments without the need to re-tune parameters for individual ice shelves. At scales of 0.5–5 km, which are typically unresolved by 3D ocean models and poorly constrained by observations, LADDIE produces plausible basal melt patterns. Most significantly, the simulated basal melt patterns are physically consistent with the applied ice shelf topography. These patterns are governed by the topographic steering and Coriolis deflection of meltwater flows, two processes that are poorly represented in basal melt parameterisations. The kilometre-scale melt patterns simulated by LADDIE include enhanced melt rates in grounding zones and basal channels and enhanced melt or freezing in shear margins. As these regions are critical for ice shelf stability, we conclude that LADDIE can provide detailed basal melt patterns at the essential resolution that ice sheet models require. The physical consistency between the applied geometry and the simulated basal melt fields indicates that LADDIE can play a valuable role in the development of coupled ice–ocean modelling.
Depth-Dependent Control in Vision-Sensor Space for Reconfigurable Parallel Manipulators

In this paper, a control approach for reconfigurable parallel robots is designed. Based on it, controls in the vision-sensor, 3D and joint spaces are designed and implemented in target tracking tasks in a novel reconfigurable delta-type parallel robot. No a priori information about the target trajectory is required. Robot reconfiguration can be used to overcome some of the limitations of parallel robots like small relative workspace or multiple singularities, at the cost of increasing the complexity of the manipulator, making its control design even more challenging. No general control methodology exists for reconfigurable parallel robots. Tracking objects with unknown trajectories is a challenging task required in many applications. Sensor-based robot control has been actively used for this type of task. However, it cannot be straightforwardly extended to reconfigurable parallel manipulators. The developed vision-sensor space control is inspired by, and can be seen as an extension of, the Velocity Linear Camera Model–Camera Space Manipulation (VLCM-CSM) methodology. Several experiments were carried out on a reconfigurable delta-type parallel robot. An average positioning error of 0.6 mm was obtained for static objectives. Tracking errors of 2.5 mm, 3.9 mm and 11.5 mm were obtained for targets moving along a linear trajectory at speeds of 6.5, 9.3 and 12.7 cm/s, respectively. The control cycle time was 16 ms. These results validate the proposed approach and improve upon previous works for non-reconfigurable robots.
Structure and Characteristics of Precipitation Systems Observed by TRMM

Multi-sensor measurements of total lightning (in-cloud plus cloud-to-ground) from the Lightning Imaging Sensor (LIS) aboard the TRMM satellite has been combined with passive microwave ice scattering and precipitation radar reflectivity profile information previously cataloged for precipitation features observed by TRMM. These precipitation features are defined by their surface rainfall or ice scattering signatures, with horizontal scales approx. 100 - 10000 sq km. Additionally, convective scale (approx. 100 sq km) storms are defined by the lightning data. Over the U.S. the national cloud-to-ground lightning observations are used to also determine the ratio of in-cloud to cloud-to-ground lightning, where it is hypothesized these ratios are related to the vertical profile of reflectivity and concentration of precipitation-sized ice. Combining the LIS, TRMM Microwave Imager (TMI), and Precipitation Radar (PR) for these storms allows investigation of the convective structures and convective regimes leading to observed lightning, scattering, and reflectivity signatures. Application of this approach to a global, multi-year data set (1998-2000) furthers our understanding of convective processes in different climatological regimes. The figure shows the distribution of high flash rate storms.
Rumor Detection in Social Media Based on Multi-Hop Graphs and Differential Time Series

The widespread dissemination of rumors (fake information) on online social media has had a detrimental impact on public opinion and the social environment. This necessitates the urgent need for efficient rumor detection methods. In recent years, deep learning techniques, including graph neural networks (GNNs) and recurrent neural networks (RNNs), have been employed to capture the spatiotemporal features of rumors. However, existing research has largely overlooked the limitations of traditional GNNs based on message-passing frameworks when dealing with rumor propagation graphs. In fact, due to the issues of excessive smoothing and gradient vanishing, traditional GNNs struggle to capture the interactive information among high-order neighbors when handling deep graphs, such as those in rumor propagation scenarios. Furthermore, previous methods used for learning the temporal features of rumors, whether based on dynamic graphs or time series, have overlooked the importance of differential temporal information. To address the aforementioned issues, this paper proposes a rumor detection model based on multi-hop graphs and differential time series. Specifically, this model consists of two components: the structural feature extraction module and the temporal feature extraction module. The former utilizes a multi-hop graph and the enhanced message passing framework to learn the high-order structural features of rumor propagation graphs. The latter explicitly models the differential time series to learn the temporal features of rumors. Extensive experiments conducted on multiple real-world datasets demonstrate that our proposed model outperforms the previous state-of-the-art methods.
CNN-assisted quantitative phase microscopy for biological cell imaging

Phase imaging is a solution for the reconstruction of phase information from intensity observations. To make phase imaging possible, sophisticated extra systems are embedded into the existing imaging systems. Contrary, we propose a phase problem solution by DCNN-based framework, which is simple in terms of an optical system. We propose to replace optical lenses with computational algorithms such as CNN phase reconstruction and wavefront propagation. The framework is tested in simulation and real-life experimental phase imaging. To have real experiments with objects close to real-life biological cells, we simulated experimental training datasets on a phase-only spatial light modulator, where phase objects are modeled with corresponding phase distribution to biological cells.
The results of experimental studies of the working body of the loader pile of fodder crops

The article substantiates the need for this study, analyzes the advantages and disadvantages of various working bodies of loading devices, as well as the results of the analysis on the prospects of a finger-type separating working body for uniform loading of a pile of seeds into dryers. The factors influencing the working process of leveling the material and the methodology of experimental research are given. The maximum number of factors influencing the process under study has been determined, the most likely areas of their change have been selected and the conditions characterizing the process of leveling the pile of fodder crops by the loader have been selected. The schemes of dependence of the coefficient of uneven leveling of the pile on the feed rate of the material and the speed of rotation of the drum, the dependence of uneven leveling on the length of the finger and the gap between them, the dependence of uneven leveling on the diameter of the drum and the number of rakes and the dependence of uneven leveling on the angle of the fingers and the thickness of the layer of the pile, as well as the influence of kinematic, structural and technological parameters of the working body are presented on the quality of leveling the pile.
Monitoring the first candidate host for the merger of a Supermassive Black Hole Binary with H.E.S.S.

Supermassive black hole binary (SMBHB) is a result of galaxies coalescing, when two supermas-sive black holes form a hard binary with distances from kpc to pc. If the system reaches milliparsec separation, the black holes eventually merge. There are a growing number of few sub-pc SMBHB candidates, one of which according to Jiang et al (2022). will merge within three years. We have performed the monitoring of the host galaxy SDSSJ143016.05+230344.4 during its visibility with H.E. S.S. in April–July 2022. Given that subsequent follow-up observations with optical and X-ray instruments have not confirmed some of the predictions initially presented, and time constraints for the merger beyond 2022 are less precise, we changed our monitoring and follow-up strategy for further observations. In this work we present our results of the monitoring and discuss the prospects of these kind of observations with imaging atmospheric Cherenkov telescopes.
Effect of mannan-rich fractions and a mixture of sodium butyrate and zinc proteinate on performance, intestinal morphometry, and gene expression in broilers

Abstract This study evaluated the effects of isolated or combined prebiotics blended with sodium butyrate and zinc proteinate on performance, intestinal morphometry, and expression of genes associated with nutrient transport and immune response in broilers. 1,400 birds were randomly assigned to 5 treatments (Negative control (NC) without antibiotic; Positive control (PC) with antibiotic; Prebiotic (Prebio) composed of mannan fractions; Blend, composed of sodium butyrate, hydrolysed yeast cell wall and zinc proteinate; and the combination Prebio + Blend), with eight replications and 35 birds per experimental unit. The PC led to higher weight gain (WG) and lowered feed conversion (FCR) from 1 to 7 days of life than the other treatments. The use of prebio and blend resulted in high WG from 22 to 42 days (1773; 1768.9 g, respectively). However, the combination of prebio + blend was similar to PC and NC treatments. The additives resulted in longer duodenal villi when administered alone and in ileal villi (p = 0.001) combined, with no effect on jejunal villi. Crypt depth and duodenal villus: crypt ratio was higher for both additives types. A significant difference among treatments in the expression of the sodium-dependent glucose transporter gene (SGLT1) was noted, with greater expression in birds that received NC. There was higher expression of the neutral and cationic amino acid transporter gene (y + LAT-2) with the prebio and blend, either alone or in combination. The prebio blend with sodium butyrate and zinc proteinate additives used separately in broiler diets supported beneficial changes in intestinal morphometry, nutrient absorption, and performance, indicating their value in antibiotic-free broiler production systems. HIGHLIGHTS The additives in the diets of broilers from 1 to 42 days resulted in beneficial performance. The additives influenced the health of the birds, with a positive result in intestinal morphometry. The prebiotic and blend additives demonstrated increased gene expression of absorption of neutral amino acids.
Mindfulness and Well-Being: Mindfulness-Based Interventions for Promoting Well-Being and its Impact on Cognitive, Emotional, and Physiological Processes

There has been a lot of interest in mindfulness-based treatments (MBIs) in recent years as a potentially effective method for increasing happiness and decreasing anxiety. The purpose of this study is to examine the research done on the positive effects of MBIs and the mechanisms by which they work. Here, we explore the research behind the claims that mindfulness-based interventions (MBIs) are successful in increasing happiness and decreasing stress. Mindfulness has been demonstrated in scientific studies to have a number of positive effects on mental health, including better focus, memory, and decision-making. Mindfulness may also help with emotional management by raising upbeat emotions while decreasing downbeat ones and decreasing stress reaction time. Reductions in stress hormones like cortisol and other physiological indicators like blood pressure and inflammation mirror these mental and emotional shifts. Additionally, randomised controlled studies show that MBIs are beneficial in lowering depressive, anxious, and stress symptoms and raising well-being outcomes including life satisfaction and resiliency. These results hold steady over time and have been seen across a wide range of groups, both clinical and non-clinical. Finally, this report emphasises the need for more study to understand the underlying processes and optimise the administration of MBIs, as well as the value of mindfulness as a viable strategy to increasing well-being and lowering stress. The results of this study have significance for the design of programmes to promote mental health and well-being across demographics.
Marine biodiversity research in the Ryukyu Islands, Japan: current status and trends

Marine biodiversity and derived ecosystem services are critical to the healthy functioning of marine ecosystems, and to human economic and societal well-being. Thus, an understanding of marine biodiversity in different ecosystems is necessary for their conservation and management. Coral reefs in particular are noted for their high levels of biodiversity, and among the world’s coral reefs, the subtropical Ryukyu Islands (RYS; also known as the Nansei Islands) in Japan have been shown to harbor very high levels of marine biodiversity. This study provides an overview of the state of marine biodiversity research in the RYS. First, we examined the amount of English language scientific literature in the Web of Science (WoS; 1995–2017) on six selected representative taxa spanning protists to vertebrates across six geographic sub-regions in the RYS. Our results show clear taxonomic and sub-region bias, with research on Pisces, Cnidaria, and Crustacea to be much more common than on Dinoflagellata, Echinodermata, and Mollusca. Such research was more commonly conducted in sub-regions with larger human populations (Okinawa, Yaeyama). Additional analyses with the Ocean Biogeographic Information System (OBIS) records show that within sub-regions, records are concentrated in areas directly around marine research stations and institutes (if present), further showing geographical bias within sub-regions. While not surprising, the results indicate a need to address ‘understudied’ taxa in ‘understudied sub-regions’ (Tokara, Miyako, Yakutane, Amami Oshima), particularly sub-regions away from marine research stations. Second, we compared the numbers of English language scientific papers on eight ecological topics for the RYS with numbers from selected major coral reef regions of the world; the Caribbean (CAR), Great Barrier Reef (GBR), and the Red Sea (RES). As expected, the numbers for all topics in the RYS were well below numbers from all other regions, yet within this disparity, research in the RYS on ‘marine protected areas’ and ‘herbivory’ was an order of magnitude lower than numbers in other regions. Additionally, while manuscript numbers on the RYS have increased from 1995 to 2016, the rate of increase (4.0 times) was seen to be lower than those in the CAR, RES, and GBR (4.6–8.4 times). Coral reefs in the RYS feature high levels of both endemism and anthropogenic threats, and subsequently they contain a concentration of some of the world’s most critically endangered marine species. To protect these threatened species and coral reef ecosystems, more data are needed to fill the research gaps identified in this study.
A Propagação Lenta de um Sinal Altimétrico Confinado à Vertente Continental da Patagónia

Coastal areas are extremely dynamic, they are characterized by the presence of periodic phenomena that are fundamental to the conservation of their ecosystems. The present work aims to study one of these phenomena, known as coastal trapped waves (CTW). CTW are developed in the regions of continental shelf and shelf break. It is propitious the existence of an extensive platform with a gentle slope of depth. The CTW are characterized by presenting a long period, which could be from several days to several weeks, and a subinercial frequency, in other words, the frequency of these waves are lower than the local inertial frequency. Another aspect to take into account is the direction of propagation of the CTW. They propagate with the coast on the left in the Southern Hemisphere and with the coast on the right in the Northern Hemisphere. In this work, we intend to evaluate the existence of coastal trapped waves in the continental shelf break of Patagonia as there were already some evidence of the presence of this phenomenon in this region. According to the work of Saraceno et al. (2005), there are several energy peaks at intraseasonal frequency, in power spectral density, related to Sea Surface Temperature (SST) and Ocean Colour (chl-a). The associated periods of these signals were nearly 70 days and 100 days. The authors have suggested the CTW as a possible mechanism leading to the variability observed. Therefore, it was considered relevant the study of the Patagonian shelf break, through the use of Remote Sensing data, based on use of altimetry data (MSLA and "Along-track") and the color data of the Ocean (SST and Chl-a). Through the use of Remote Sensing data, were made time series, with their respective Fourier transforms, in order to analyze the periodicity of the phenomenon. They were also performed several Hovmoller diagrams, to analyze the propagation of altimetric and color signals, which were used to calculate the signal propagation speed, by applying the Radon transform. In addition to the methodologies associated with Remote Sensing, it was also applied a model developed by K. Brink (1982), used to study the CTW. In regard to results, it is possible to confirm that there is an altimeter signal propagating, slowly, along the continental shelf break, with a phase velocity 0.3 m/s. However, it is not possible to ensure that there is a CTW propagation as the signal is associated with a high mode (level) of CTW.
Validation test of Monte Carlo codes employed in biomedical optics applications

The Monte Carlo (MC) method is a gold standard for "solving" the radiative transport equation even in complex geometries and distributions of optical properties. The exact analytical benchmark provided by the invariant total mean path length law spent by light injected with uniform Lambertian illumination within nonabsorbing scattering media is used to verify Monte Carlo codes developed for biomedical optics applications. The correctness of an MC code can be evaluated with a sample t-test. In addition, the invariance of the mean path length ensures that the expected value is known regardless of the complexity of the medium. The accuracy of the estimated mean path length can progressively increase as the number of simulated trajectories increases. The method can be used regardless of the scattering and geometric properties of the medium, as well as in the presence of refractive index mismatch between the medium and the outer region and between different regions of the medium. The proposed method is particularly reliable for detecting inaccuracies in the treatment of finite media boundaries. The results presented in this contribution, obtained with a standard computer, show a verification of our MC code to the sixth decimal place. This method can provide a fundamental tool for verification of Monte Carlo codes in the geometry of interest without resorting to simpler geometries and uniform distribution of the scattering properties.
Path Loss in Directional Antennas for 5G Millimeter-Wave Communications

: High date rate and huge bandwidth Millimeter wave systems suf- fers from poor link budget due to the blockage of the millimeter wave signal by the obstacles. Directional antenna which guarantees signal delivery if line of sight communication between the transmitter and receiver exists with the improvement in a signal strength. Multi Input Multi Output (MIMO) beamforming uses channel statistics to guide the beam improving the multiplexing gain and beamforming gain. In this paper, Evaluation of the equivalent omnidirectional antenna pattern and omnidirectional received power are calculated by summing the received powers from all measured unique pointing angles recived at antenna halfpower beamwidth step increments in the azimuth and elevation planes, By demon- strating that the synthesized omnidirectional received power and path loss this method is validated and are independent of antenna beamwidth, through theoretical analyses and millimeter-wave propagation measurements using an- tennas with different beamwidths. The method provide accurate results while increasing the measurement range substantially through the use of directional antennas.
Classification of Crop Disease Images Based on Convolutional Neural Network

Agriculture is the cornerstone of human survival and affects everyone. Crop diseases are crucial factors that impact crop yields. However, manually diagnosing crop diseases requires specialized knowledge and is prone to high error rates, consuming significant time and societal resources. It also hinders the development of modernized agriculture. Therefore, this paper proposes a Mobile-SKF Net model for crop disease image classification based on MobileNet v2. The Mo-bile-SKF Net model is built upon the MobileNet v2 model, incorporating channel attention modules to enhance feature representation, followed by classification output. Data augmentation and transformations are applied to the dataset, which is then used for training the Mobile-SKF Net model. The model is validated through experiments. Experimental results demonstrate that the Mobile-SKF Net achieves a crop classification accuracy of 99.41% on the public dataset PlantVillage, exhibiting excellent performance evaluation metrics and accuracy. The Mobile-SKF Net serves as a basis for crop disease identification, providing valuable insights in this field.