Miracle-dz/UniFAR-FTUs huggingface dataset:
Teneurs en tanins de 15 ligneux fourragers du Burkina Faso

Face au recul progressif du fourrage herbace, le betail des villages de Diarabakoko et de Dionona est contraint en saison seche de s’alimenter plus de fourrage des ligneux. Mais les teneurs en facteurs antinutritionnels particulierement en tanins condenses de certaines especes ligneuses peuvent limiter la consommation de leurs fourrages. L’objectif de l’etude est de caracteriser et quantifier les tanins contenus dans les feuilles et/ou fruits de 15 ligneux fourragers couramment appetes. Les tanins ont ete quantifies par spectrometrie d’absorption UV-Vis a la longueur d’onde de 760 nm. Les tanins condenses ont ete identifies dans 53,33% des especes etudiees avec des teneurs significativement differentes (P ˂ 0,05). Les teneurs des feuilles et des fruits ont varie respectivement de 0,810 ± 0,041 a 7,102 ± 0,117 g EAT/100 g MS et de 3,016 ± 0,056 a 8,074 ± 0,042 g EAT/100 g MS. Les teneurs en tanins galliques des feuilles ont oscille entre 0,214 ± 0,006 et 3,627 ± 0,072 g EAT/100 g MS et celles des fruits entre 2,153 ± 0,006 et 2,380 ± 0,039 g EAT/100 g MS. Le fourrage des especes etudiees sauf les feuilles de Acacia sieberiana et les fruits de Cassia sieberiana peuvent contribuer a la supplementation des ruminants. Les teneurs en tanins peuvent servir de critere de choix supplementaire des ligneux fourragers en amenagement pastoral et en agroforesterie. Mots-cles : Burkina Faso, ligneux fourragers, metabolites secondaires, tanins, teneurs, facteurs antinutritionnels. Tannins content of 15 woody forages from Burkina Faso Facing the progressive decline of herbaceous forage, ruminant animals from the villages of Diarabakoko and Dionona are forced in the dry season to feed more browse forages. But the levels of anti-nutritional factors particularly condensed tannins of some browses species may limit their consumption. The objective of the study was to characterize and quantify the tannins in the leaves and/or fruits of 15 common woody forage palatable. Tannins have been quantified by spectrophotometry UV-Vis absorption at wavelength of 760 nm. Condensed tannins were identified in 53.33% of the species studied with significantly different levels (P ˂ 0.05). The contents of leaves and fruits ranged respectively 0.810 ± 0.041 to 7.102 ± 0.117 g TAE/100 g DM and 3,016 ± 0.056 to 8.074 ± 0.042 g TAE/100 g DM. The contents of gallic tannins in leaves varied between 0.214 ± 0.006 and 3.627 ± 0.072 g TAE/100 g DM and those in fruits were between 2.153 ± 0.006 and 2.380 ± 0.039 g TAE/100 g DM. Forage species studied except the leaves of Acacia sieberiana and fruits of Cassia sieberiana can contribute to the supplementation of ruminants. Tannins content can be used as a supplementary criterion for selection of tree fodder in pasture management and in agroforestry. Keywords : Burkina Faso, browses, secondary metabolites, tannins, content, anti-nutritional factors.
Influenza hospitalisations in Spain between the last influenza and COVID-19 pandemic (2009–2019)

Abstract Knowing the burden of severe disease caused by influenza is essential for disease risk communication, to understand the true impact of vaccination programmes and to guide public health and disease control measures. We estimated the number of influenza-attributable hospitalisations in Spain during the 2010–2011 to 2019–2020 seasons – based on the hospitalisations due to severe acute respiratory infection (SARI) in Spain using the hospital discharge database and virological influenza information from the Spanish Influenza Sentinel Surveillance System (SISSS). The weekly numbers of influenza-attributable hospitalisations were calculated by multiplying the weekly SARI hospitalisations by the weekly influenza virus positivity, obtained from the SISSS in each season, stratified by age group and sex. The influenza-related hospitalisation burden is age-specific and varies significantly by influenza season. People aged 65 and over yielded the highest average influenza-attributable hospitalisation rates per season (615.6 per 100,000), followed by children aged under 5 (251.2 per 100,000). These results provide an essential contribution to influenza control and to improving existing vaccination programmes, as well as to the optimisation and planning of health resources and policies.
Using seismic inversion and net pay to calibrate Eagle Ford Shale producible resources

AbstractWe found a strong correlation between the estimated production volume and hydrocarbon resources in thicker and more porous intervals in the Eagle Ford Shale through integrated petrophysical and engineering analysis. The wells analyzed were selected with similar operational designs so that the rock properties were the main variables impacting the production volume. Seismic data were used to characterize such desired rock properties, including thickness and porosity, to evaluate the producing potentials across the field. Seismic interpretation provided the top and base of the Eagle Ford reservoir, and hence, its thickness. Seismic inversion calibrated the acoustic impedance. Also, the seismic net pay estimation method predicted the thickness of the more porous intervals. The calculated seismic net pay agreed with the well log data. As petrophysical analysis suggested, the seismic net pay also formed a strong correlation with the production volume and has been used to predict the producible resources.
Celebrating cultural diversity : implementing an integrated approach to arts and culture in the intermediate phase of curriculum 2005

Since its inception, educators across the board in South Africa have struggled to implement the new curriculum. Initial problems with terminology and availability of learning materials have been addressed, but still the resistance to Outcomes Based Education (0BE) and Curriculum 2005 (C2005) continues. Some of the reasons for the resistance point to feelings of disempowerment experienced by generalist and specialist educators who now have to teach the new Learning Area Arts and Culture. This has been attributed to, amongst others, a lack of training, resulting in feelings of inadequacy, inappropriate training for large multicultural classes and the lack of teaching resources. Another reason for the resistance has been described as a resistance to change. Many educators have found it difficult to make the paradigm shift from the previous educational system to OBE and C2005. The aim of the study is to research and explore ways of empowering educators to teach Arts and Culture. The new educational system is geared to redressing the imbalances of the past and giving more expression to the diversity of cultures represented in South African schools. Whereas the previous system was founded on exclusively Eurocentric ideology, principles and values, the new system aims at a more inclusive Afrocentric approach. However, criticisms leveled at C2005 have suggested that it is still basically Western in terms of values, terminology and methodology. This study is therefore aimed at investigating a culturally diverse music/arts curriculum, which draws on the wealth of resources, methods and modes readily accessible in South Africa. A comprehensive literature review guides the study towards a greater understanding of how cultural identities are formed out of a need to belong and how important recognition is to individuals and groups, particularly in terms of their diverse cultural expressions. Music and the arts are understood as being vitally important channels for expression of this diversity. Yet, true to the Afrocentric principle of holism, unity is found in diversity. As much common ground exists between an integrated approach and an Afrocentric approach to music/arts education, these principles are explored to determine whether they can be adapted for use in contemporary South African classrooms. An integrated project mode, which provides a balance between the specific knowledge contexts of the various Learning Areas and collaborative learning aimed at developing the natural links between learning areas to create a vibrant whole, is suggested. The researcher conducted an integrated project at her school with the common theme of "District Six" linking four Learning Areas and their components. Participatory action research using qualitative methods such as questionnaires were used to determine the feasibility of an integrated project mode of learning as a means of empowering educators to teach Arts and Culture. Subsequently recommendations were made regarding implementation.
Nitrous Oxide Emissions from Agricultural Toposequences in Alberta and Saskatchewan

Nitrous oxide fluxes from soils are inherently variable in time and space. An improved understanding of this variability is needed to make accurate estimates of N 2 O fluxes at a regional scale. The objectives of this work were to (i) characterize the influence of soillandscape combinations and N application rates on N 2 O emissions and to (ii) determine the contribution of these influences on the estimation of N 2 O emissions at the field scale. We used static chambers and gas chromatography methods to measure N 2 O fluxes and collected ancillary data (mineral N, water soluble C, soil water content, soil temperature) in Canada at Mundare (AB) in the aspen parkland ecoregion and at Swift Current (SK) in the short-grass prairie ecoregion. At Mundare, measurements were taken in 1995 and 1996 by landscape position and land use. At Swift Current, data were collected in 1999 and 2000 by landscape position and N rate. At Mundare, landscape position affected N 2 O emissions but the pattern varied seasonally. During a 46-d period in summer 1995, a flux of 430 g N 2 O-N ha -1 measured in a backslope was greater than the 60 g N 2 O-N ha measured on average in shoulder and depressional areas. The flux pattern changed during a 43-d spring thaw of 1996 when fluxes from depressional areas were greatest (1710 g N 2 O-N ha -1 ). Nitrous oxide emissions from natural areas were small. The emission pattern during summer 1996 was similar to that of 1995 but the fluxes were an order of magnitude larger. At Swift Current, N 2 O fluxes in summer 1999 were affected by topography and N rate. Fluxes were greatest in depressional areas receiving N at 110 kg ha -1 (3140 g N 2 O-N ha -1 ). Use of the area fraction occupied by each landscape position to calculate N 2 O flux increased the estimates of N 2 O fluxes at the field scale in five out of six cases. Further research of N 2 O fluxes in variable landscapes should help elucidate factors controlling N 2 O fluxes from pedon to field scale and thus translate into improved flux estimates at regional scales.
Evaluation of livestock farmers’ knowledge, attitudes and practices regarding the use of veterinary vaccines in Southwest Ethiopia

Abstract Background The utilization of veterinary vaccines plays a vital role in preventing and managing animal diseases. However, the success of vaccination programmes relies on livestock farmers’ understanding, perspectives and behaviours regarding their application. Therefore, this study aims to evaluate the knowledge, attitudes and practices of livestock farmers in Southwest Ethiopia regarding the use of veterinary vaccines. Methods The study followed a cross‐sectional design conducted between October 2021 and October 2022. A sample of 476 livestock‐owning farmers, including those who raise dairy cattle, beef cattle and poultry, were interviewed from the districts of Shei Bench, Semen Bench, Sheko and Yeki. Results The findings revealed that participants from Sheko, who had a poultry farm, were college graduates and resided in an urban area, were more likely to have good knowledge of veterinary vaccines. Similarly, participants who were male, from Semen Bench, had a poultry farm and had a high school education, exhibited a positive attitude towards veterinary vaccines. Furthermore, being male, from Semen Bench, having a poultry farm, and having a high school education were associated with increased veterinary vaccine use. Conclusion This study highlights the importance of addressing gender differences and tailoring interventions based on geography and farming conditions in the area. These measures are crucial to improve practices related to veterinary vaccines for enhanced animal health and productivity. Prioritizing education, veterinary services and information dissemination is vital. However, further research and targeted interventions are needed to better comprehend underlying factors and implement effective strategies for diverse communities in different areas.
AdaMerging: Adaptive Model Merging for Multi-Task Learning

Multi-task learning (MTL) aims to empower a model to tackle multiple tasks simultaneously. A recent development known as task arithmetic has revealed that several models, each fine-tuned for distinct tasks, can be directly merged into a single model to execute MTL without necessitating a retraining process using the initial training data. Nevertheless, this direct addition of models often leads to a significant deterioration in the overall performance of the merged model. This decline occurs due to potential conflicts and intricate correlations among the multiple tasks. Consequently, the challenge emerges of how to merge pre-trained models more effectively without using their original training data. This paper introduces an innovative technique called Adaptive Model Merging (AdaMerging). This approach aims to autonomously learn the coefficients for model merging, either in a task-wise or layer-wise manner, without relying on the original training data. Specifically, our AdaMerging method operates as an automatic, unsupervised task arithmetic scheme. It leverages entropy minimization on unlabeled test samples from the multi-task setup as a surrogate objective function to iteratively refine the merging coefficients of the multiple models. Our experimental findings across eight tasks demonstrate the efficacy of the AdaMerging scheme we put forth. Compared to the current state-of-the-art task arithmetic merging scheme, AdaMerging showcases a remarkable 11\% improvement in performance. Notably, AdaMerging also exhibits superior generalization capabilities when applied to unseen downstream tasks. Furthermore, it displays a significantly enhanced robustness to data distribution shifts that may occur during the testing phase.
Online Constraint Tightening in Stochastic Model Predictive Control: A Regression Approach

Solving chance-constrained stochastic optimal control problems is a significant challenge in control. This is because no analytical solutions exist for up to a handful of special cases. A common and computationally efficient approach for tackling chance-constrained stochastic optimal control problems consists of reformulating the chance constraints as hard constraints with a constraint-tightening parameter. However, in such approaches, the choice of constraint-tightening parameter remains challenging, and guarantees can mostly be obtained assuming that the process noise distribution is known a priori. Moreover, the chance constraints are often not tightly satisfied, leading to unnecessarily high costs. This work proposes a data-driven approach for learning the constraint-tightening parameters online during control. To this end, we reformulate the choice of constraint-tightening parameter for the closed-loop as a binary regression problem. We then leverage a highly expressive \gls{gp} model for binary regression to approximate the smallest constraint-tightening parameters that satisfy the chance constraints. By tuning the algorithm parameters appropriately, we show that the resulting constraint-tightening parameters satisfy the chance constraints up to an arbitrarily small margin with high probability. Our approach yields constraint-tightening parameters that tightly satisfy the chance constraints in numerical experiments, resulting in a lower average cost than three other state-of-the-art approaches.
Peripheral helper T cells, mavericks of peripheral immune responses

Abstract Peripheral helper T (Tph) cells have been established, through intensive efforts to elucidate local immune responses in human rheumatoid arthritis (RA), as a CD4 subset intimately involved in acquired immunity in peripheral tissues. Initially, Tph cells were noted as a CD4 population that produces high levels of CXCL13 in RA synovial tissues, followed by a demonstration of their ability to help B cells. In contrast to follicular helper T (Tfh) cells, Tph cells do not express the transcription factor BCL6 but express molecules such as CXCL13, interleukin (IL)-21, and inducible T-cell costimulator (ICOS) to help B cells in peripheral tissues. Subsequent studies showed that Tph cells are associated with various diseases, including autoimmune diseases, infections, and malignancies, and with the development of early life immunity. This review summarizes the phenotype and function of Tph cells in RA and discusses their differentiation and diversity in various conditions.
CoDA: Collaborative Novel Box Discovery and Cross-modal Alignment for Open-vocabulary 3D Object Detection

Open-vocabulary 3D Object Detection (OV-3DDet) aims to detect objects from an arbitrary list of categories within a 3D scene, which remains seldom explored in the literature. There are primarily two fundamental problems in OV-3DDet, i.e., localizing and classifying novel objects. This paper aims at addressing the two problems simultaneously via a unified framework, under the condition of limited base categories. To localize novel 3D objects, we propose an effective 3D Novel Object Discovery strategy, which utilizes both the 3D box geometry priors and 2D semantic open-vocabulary priors to generate pseudo box labels of the novel objects. To classify novel object boxes, we further develop a cross-modal alignment module based on discovered novel boxes, to align feature spaces between 3D point cloud and image/text modalities. Specifically, the alignment process contains a class-agnostic and a class-discriminative alignment, incorporating not only the base objects with annotations but also the increasingly discovered novel objects, resulting in an iteratively enhanced alignment. The novel box discovery and crossmodal alignment are jointly learned to collaboratively benefit each other. The novel object discovery can directly impact the cross-modal alignment, while a better feature alignment can, in turn, boost the localization capability, leading to a unified OV-3DDet framework, named CoDA, for simultaneous novel object localization and classification. Extensive experiments on two challenging datasets (i.e., SUN-RGBD and ScanNet) demonstrate the effectiveness of our method and also show a significant mAP improvement upon the best-performing alternative method by 80%. Codes and pre-trained models are released on the project page.
A generalized spectral correspondence

We establish a strong categorical correspondence between isomorphism classes of sheaves of arbitrary rank on one algebraic curve and twisted pairs on another algebraic curve. In a particular application, we realize a generic elliptic curve as a spectral cover of the complex projective line $\mathbb{P}^1$ and then construct examples of semistable co-Higgs bundles over $\mathbb{P}^1$ as pushforwards of locally-free sheaves of certain small ranks over the elliptic curve. By appealing to a composite push-pull projection formula, we conjecture an iterated version of the spectral correspondence. We prove this conjecture for a particular class of spectral covers of $\mathbb {P}^1$. The proof relies upon a classification of Galois groups into primitive and imprimitive types. In this context, we revisit a century-old theorem of J.F. Ritt.
Provable Tensor Completion with Graph Information

Graphs, depicting the interrelations between variables, has been widely used as effective side information for accurate data recovery in various matrix/tensor recovery related applications. In this paper, we study the tensor completion problem with graph information. Current research on graph-regularized tensor completion tends to be task-specific, lacking generality and systematic approaches. Furthermore, a recovery theory to ensure performance remains absent. Moreover, these approaches overlook the dynamic aspects of graphs, treating them as static akin to matrices, even though graphs could exhibit dynamism in tensor-related scenarios. To confront these challenges, we introduce a pioneering framework in this paper that systematically formulates a novel model, theory, and algorithm for solving the dynamic graph regularized tensor completion problem. For the model, we establish a rigorous mathematical representation of the dynamic graph, based on which we derive a new tensor-oriented graph smoothness regularization. By integrating this regularization into a tensor decomposition model based on transformed t-SVD, we develop a comprehensive model simultaneously capturing the low-rank and similarity structure of the tensor. In terms of theory, we showcase the alignment between the proposed graph smoothness regularization and a weighted tensor nuclear norm. Subsequently, we establish assurances of statistical consistency for our model, effectively bridging a gap in the theoretical examination of the problem involving tensor recovery with graph information. In terms of the algorithm, we develop a solution of high effectiveness, accompanied by a guaranteed convergence, to address the resulting model. To showcase the prowess of our proposed model in contrast to established ones, we provide in-depth numerical experiments encompassing synthetic data as well as real-world datasets.
Parameter estimation by learning quantum correlations in continuous photon-counting data using neural networks

We present an inference method utilizing artificial neural networks for parameter estimation of a quantum probe monitored through a single continuous measurement. Unlike existing approaches focusing on the diffusive signals generated by continuous weak measurements, our method harnesses quantum correlations in discrete photon-counting data characterized by quantum jumps. We benchmark the precision of this method against Bayesian inference, which is optimal in the sense of information retrieval. By using numerical experiments on a two-level quantum system, we demonstrate that our approach can achieve a similar optimal performance as Bayesian inference, while drastically reducing computational costs. Additionally, the method exhibits robustness against the presence of imperfections in both measurement and training data. This approach offers a promising and computationally efficient tool for quantum parameter estimation with photon-counting data, relevant for applications such as quantum sensing or quantum imaging, as well as robust calibration tasks in laboratory-based settings.