Classification and mapping of the woody vegetation of Gonarezhou National Park, Zimbabwe

Within the framework of the Great Limpopo Transfrontier Conservation Area (GLTFCA), the purpose of this study was to produce a classification of the woody vegetation of the Gonarezhou National Park, Zimbabwe, and a map of its potential distribution. Cover-abundance data of woody species were collected in 330 georeferenced relevés across the Park. These data were used to produce two matrices: the first one using the cover-abundance values as collected in five height layers and the second one based on merging the layers into a single cover value for each species. Automatic classifications were produced for both matrices to determine the optimal number of vegetation types. The two classification approaches both produced 14 types belonging to three macro-groups: mopane, miombo and alluvial woodlands. The results of the two classifications were compared looking at the constant, dominant and diagnostic species of each type. The classification based on separate layers was considered more effective and retained. A high-resolution map of the potential distribution of vegetation types for the whole study area was produced using Random Forest. In the model, the relationship between bioclimatic and topographic variables, known to be correlated to vegetation types, and the classified relevés was used. Identified vegetation types were compared with those of other national parks within the GLTFCA, and an evaluation of the main threats and pressures was conducted. Conservation implications: Vegetation classification and mapping are useful tools for multiple purposes including: surveying and monitoring plant and animal populations, communities and their habitats, and development of management and conservation strategies. Filling the knowledge gap for the Gonarezhou National Park provides a basis for standardised and homogeneous vegetation classification and mapping for the entire Great Limpopo Transfrontier Conservation Area

Interdenominational Cooperation in Religious New Media Projects: the Case of the Christian Media Center

Abstract: In the last decade, macro religious institutions have undergone a process of digitalisation that enabled them to incorporate Internet Communication Technologies in their organisational infrastructure. Stemming from digital religion scholarship, the research presented in this paper relate to a study of the philosophy and functioning of an innovative Catholic media enterprise called Christian Media Center (CMC). Based in Israel and the Occupied Palestinian Territories, the CMC was established through the cooperation between the long-standing Franciscan Order and the technology-savvy Brazilian community of Canção Nova. Accordingly, this paper asks: which forms of interdenominational negotiation are involved in the functioning of the CMC? Drawing on interviews conducted during three years, this research will outline the process of internal negotiation required by the development of this Catholic new media project and propose possible directions for future research

Biological Random Walks: multi-omics integration for disease gene prioritization

Motivation: Over the past decade, network-based approaches have proven useful in identifying disease modules within the human interactome, often providing insights into key mechanisms and guiding the quest for therapeutic targets. This is all the more important, since experimental investigation of potential gene candidates is an expensive task, thus not always a feasible option. On the other hand, many sources of biological information exist beyond the interactome and an important research direction is the design of effective techniques for their integration. Results: In this work, we introduce the Biological Random Walks (BRW) approach for disease gene prioritization in the human interactome. The proposed framework leverages multiple biological sources within an integrated framework. We perform an extensive, comparative study of BRW's performance against well-established baselines. Availability and implementation: All code is publicly available and can be downloaded at \url{https://github.com/LeoM93/BiologicalRandomWalks}. We used publicly available datasets, details on their retrieval and preprocessing are provided in the supplementary material

Milk quality of Assaf ewes raised in central Italy (Tuscany)

Introduction: The demand from outside Italy for Italian cheeses made from sheep milk has recently increased. Due to the agricultural productivity crisis, thousands of dairy farms have closed down. In the farms that have remained, there has been a tendency to increase the average milk production. Thus, in Italy there has been a recent increase in the importation of foreign high-yielding sheep breeds. Aim: this study focuses on the Assaf breed imported from Spain, which is being used to replace traditional breeds. The milk yield and quality from the Assaf sheep were monitored during lactation. Materials and methods: Ten pluriparous Assaf ewes underwent milk sampling. Milk quality, fatty acid composition and coagulation properties were analysed from day 20 to day 170 of lactation. Results and discussion: The Assaf sheep showed a high production capacity (about 1.3+0.50 litres / day, on the average) but lower percentage of fat and protein than Assaf reared in other Mediterranean Countries and than local breeds. The coagulation properties (k20 and a30) were better at the end of lactation (k20=1.37 min, a30=36.51 mm). In this phase, the increase in saturated fatty acids and medium chain fatty acids, the decrease in monounsaturated, and saturated: unsaturated fatty acid ratio, indicated a poorer milk nutritional quality in this period. Conclusions: We confirmed the high productivity of the Assaf sheep. The nutritional quality of its milk fat seems better at the beginning of lactation when less saturated, and more monounsaturated fatty acids are present in the milk. Furthermore, higher protein and better coagulation properties of the milk were observed at the end of lactatio

Evaluation of pet animals involved in assisted interventions (AAI) as potential carriers of bacteria resistant to antimicrobials: Preliminary data

open8noopenDotto, G.; Pasotto, D.; Poser, H.; Menandro, M.L.; Berlanda, M.; Falomo, M.E.; Mondin, A.; Martini, M.Dotto, Giorgia; Pasotto, Daniela; Poser, Helen; Menandro, MARIA LUISA; Berlanda, Michele; Falomo, MARIA ELENA; Mondin, Alessandra; Martini, Marc

IS GLUTATHIONE TRANSFERASE (GST) ACTIVITY IN POSIDONIA OCEANICA A STRESS RESPONSE TO MERCURY EXPOSURE?

International audienceToday, efficient monitoring of the environment is increasingly depend on the use of bio-indicator species. Marine phanerogams, and in particular Posidonia oceanica, would appear to be potentially valuable bioindicators of metal pollutants. Although correlations have been found between the mercury levels accumulated in the plant tissue and the concentrations of this metal in the water column, it would be of interest to identify early signs of the stress response induced by this xenobiotic. Thus, mercury concentrations and GST activity in Posidonia oceanica (L.) Delile from contaminated and pristine sites were measured. These results demonstrate that an increase in mercury level is correlated with an increase in GST activity, particularly in the sheaths of P. oceanica shoots. The sites contaminated by mercury were also those sites for which the highest enzyme activity was recorded. An even better correlation was found between the mercury levels and GST activity, if a 2 mo lag in the effect of mercury on GST activity is assumed

Loss of cd45 protein in canine small clear cell/t-zone lymphoma is due to absence of gene transcription.

Canine small clear cell/T-zone lymphoma (TZL) is a peculiar lymphoma subtype characterized by an indolent clinical course and aberrant CD45-negative phenotype, easily recognized by flow cytometry (FC). Recent studies have described clinical presentation and behavior, but to date the mechanisms for CD45-negativity have never been investigated.Aim of this study is to confirm the lack of surface protein using a different technique from FC and to investigate if CD45-absence in TZL is linked to the lack of the corresponding transcript and gene.40 TZL cases and 17 controls (7 T-high grade lymphoma, 10 reactive lymphnodes) were included in the present study. Immunohistochemistry was performed with a different antibody respect with FC to confirm CD45 surface protein absence. Total RNA and genomic DNA were extracted from lymph-nodes aspirates. CD45 transcript amount was investigated by quantitative real-time RT-PCR and the corresponding gene fragment was analyzed by quantitative real-time PCR. ΔΔCt method was used for the relative quantification of transcript amount and DNA load compared to housekeeping genes.All TZL cases were negative for CD45 at immunohistochemistry. CD45 transcript amount was significantly lower in TZL compared to controls (p=0.000). This difference was not significant (p=0.584) for CD45 DNA load, that was similar between TZL and controls.These results highlight that CD45 protein is lacking on cell surface and gene transcription is absent in TZL, whereas the corresponding gene is not deleted. The data here reported support further studies for clarifying possible genomic or epigenomic factors involving CD45 gene transcription and for better clarifying the possible role of CD45 in lymphomagenesis

On the Query Strategies for Efficient Online Active Distillation

Deep Learning (DL) requires lots of time and data, resulting in high computational demands. Recently, researchers employ Active Learning (AL) and online distillation to enhance training efficiency and real-time model adaptation. This paper evaluates a set of query strategies to achieve the best training results. It focuses on Human Pose Estimation (HPE) applications, assessing the impact of selected frames during training using two approaches: a classical offline method and a online evaluation through a continual learning approach employing knowledge distillation, on a popular state-of-the-art HPE dataset. The paper demonstrates the possibility of enabling training at the edge lightweight models, adapting them effectively to new contexts in real-time