Miracle-dz/UniFAR-FTUs huggingface dataset:
Système d'information de l'observatoire ReefTEMPS : données de température côtière du Pacifique Sud et Sud-Ouest

Donnees de temperature cotiere du Pacifique Sud et Sud-Ouest ReefTEMPS est un reseau de capteurs de temperature des eaux cotieres de differents etats insulaires du Pacifique Sud et Sud-Ouest pour le suivi a long terme du changement climatique et de ses effets sur l'etat des recifs coralliens et de leurs ressources. Le systeme d'information SI-TEC-PSO permet la gestion et la valorisation de ces donnees d'observation. La genericite du SI permet egalement de gerer d'autres variables issues de nouveaux capteurs. En chiffres 18 pays 21 M de mesures 104 plateformes serie de donnees cycle de mesure Architecture orientee services suite de donnees d'observation issues d'un instrument sur une plateforme donnee et une periode continue regroupement de donnees d'observation, par agregation de plusieurs cycles, ayant meme plateforme, parametre physique, niveau de qualification de donnees et famille d'instrument THREDDS Serveur de donnees grillees (netCDF) Apache/Python Serveur web dap2csv dap2graph DB-oceano • redondance des metadonnees dans le schema « md-diffusion » • mise a plat des series de donnees en fichier netCDF schema md-diffusion Optimisations pour la volumetrie Apache Tomcat Serveur web DB-oceano fichiers netCDF organises en series fichier netCDF representant un cycle de mesure Importation GET sos? request=DescribeSensor Administration, traitement par les oceanographes Remerciements • Au pole Informatique Scientifique et Appui aux partenaires du Sud de la DSI de l'IRD qui a soutenu le projet dans le cadre de SPIRALES (Soutien aux Projets InfoRmAtiques dans Les Equipes Scientifiques) • Au reseau R&D 52°North pour ses avancees sur les standards Sensor Web Enablement (SWE). Le client web de ReefTEMPS est base sur leur client libre : ThinSweClient 2.0. • Aux societes Apside et Geomatys pour leur contribution aux developpements (respectivement DB-oceano et Constellation) GET csw GET wms? request=GetMap GET sos? request=DescribeSensor GET dap2csv
Underweight Mobility-Type Pre-Frailty/ Frailty Was Associated with Complex Care Needs of Long-Term Care Facilities Residents: Results Using MDS RAP Triggers

Methods: This cross-sectional study recruited subjects aged 80 years and over from two veterans homes in Taiwan. Complexity of care was evaluated by the Resident Assessment Protocol (RAP) triggers derived from Minimum Data Set (MDS). High complexity of care needs was defined as ≥4 RAP triggers. Mobility-type pre-frailty/frailty was defined as low handgrip or slow gait speed (cutoff point defined by Asian Working Group for Sarcopenia).
A Survey on Challenges and Advances in Natural Language Processing with a Focus on Legal Informatics and Low-Resource Languages

The field of Natural Language Processing (NLP) has experienced significant growth in recent years, largely due to advancements in Deep Learning technology and especially Large Language Models. These improvements have allowed for the development of new models and architectures that have been successfully applied in various real-world applications. Despite this progress, the field of Legal Informatics has been slow to adopt these techniques. In this study, we conducted an extensive literature review of NLP research focused on legislative documents. We present the current state-of-the-art NLP tasks related to Law Consolidation, highlighting the challenges that arise in low-resource languages. Our goal is to outline the difficulties faced by this field and the methods that have been developed to overcome them. Finally, we provide examples of NLP implementations in the legal domain and discuss potential future directions.
Integrating Artificial Intelligence and PET Imaging for Drug Discovery: A Paradigm Shift in Immunotherapy

The integration of artificial intelligence (AI) and positron emission tomography (PET) imaging has the potential to become a powerful tool in drug discovery. This review aims to provide an overview of the current state of research and highlight the potential for this alliance to advance pharmaceutical innovation by accelerating the development and deployment of novel therapeutics. We previously performed a scoping review of three databases (Embase, MEDLINE, and CENTRAL), identifying 87 studies published between 2018 and 2022 relevant to medical imaging (e.g., CT, PET, MRI), immunotherapy, artificial intelligence, and radiomics. Herein, we reexamine the previously identified studies, performing a subgroup analysis on articles specifically utilizing AI and PET imaging for drug discovery purposes in immunotherapy-treated oncology patients. Of the 87 original studies identified, 15 met our updated search criteria. In these studies, radiomics features were primarily extracted from PET/CT images in combination (n = 9, 60.0%) rather than PET imaging alone (n = 6, 40.0%), and patient cohorts were mostly recruited retrospectively and from single institutions (n = 10, 66.7%). AI models were used primarily for prognostication (n = 6, 40.0%) or for assisting in tumor phenotyping (n = 4, 26.7%). About half of the studies stress-tested their models using validation sets (n = 4, 26.7%) or both validation sets and test sets (n = 4, 26.7%), while the remaining six studies (40.0%) either performed no validation at all or used less stringent methods such as cross-validation on the training set. Overall, the integration of AI and PET imaging represents a paradigm shift in drug discovery, offering new avenues for more efficient development of therapeutics. By leveraging AI algorithms and PET imaging analysis, researchers could gain deeper insights into disease mechanisms, identify new drug targets, or optimize treatment regimens. However, further research is needed to validate these findings and address challenges such as data standardization and algorithm robustness.
Effects of a music therapy and music listening intervention for nursing home residents with dementia: a randomized controlled trial

Introduction The aim of the present study was to evaluate the effects of an individual music therapy intervention and an individual music listening intervention on neuropsychiatric symptoms and quality of life in people with dementia living in a nursing home and on professional caregiver’s burden to be able to make statements about their specific value of application in clinical practice. Methods A multicenter single blind randomized controlled trial with three groups was performed: an individual music therapy intervention (IMTI) group (n = 49), an individual music listening intervention (IMLI) group (n = 56) and a control group (n = 53) receiving usual care. The interventions were given during three weeks, three times a week on non-consecutive days during 30–45 minutes for in total nine sessions. The endpoint of the study is the difference from baseline to interim (1,5 week), post-intervention (3 weeks) and follow-up (6 weeks) in reported scores of problem behaviour (NPI-NH) and quality of life (Qualidem) in people with dementia and occupational disruptiveness (NPI-NH) in care professionals. Results In total 158 people with dementia were randomized to one of the two intervention groups or the control group. Multilevel analyses demonstrated that hyperactive behaviour assessed by the NPI-NH was significantly more reduced for the IMLI group at follow up and that restless behaviour assessed by the Qualidem was significantly more reduced for the IMTI group at post and follow-up measurement compared to the control group. No significant effects between groups were found in other NPI-NH clusters or Qualidem subscales. Conclusion In conclusion, because we found no convincing evidence that the IMTI or IMLI is more effective than the other both interventions should be considered in clinical practice. For the future, we advise further research into the sustainability of the effects with alternative designs, like a single case experimental design.
A Non-Intrusive Load Identification Method Based on Multi-Head Attention

Non-intrusive load identification plays a crucial role in developing a green and low-carbon energy supply and demand mechanism. Among the various load identification technologies, the low-frequency electrical signal load identification stands out due to its ability to discern user’s electricity consumption habits without increasing the user’s hardware cost, thus presenting promising application prospects. However, the challenge lies in the scarcity of available data and the uneven distribution of samples, resulting in reduced accuracy. In this paper, we present a non-intrusive load state identification method based on the combination of LSTM model and multi-head attention model. By fusing those two techniques, the model can extract and utilize richer and more essential intrinsic features in electrical signals. The use of focal loss can balance the weight importance of different states with significantly different sample numbers. The experimental results on two open data-set show that the proposed algorithm can considerably improve the identification accuracy compared to other NILM methods, and the method also has good practical value in real application.
Development of Biotinylated Liposomes Encapsulating Metformin for Therapeutic Targeting of Inflammation-Based Diseases

Inflammation is a physiological response to a damaging stimulus but sometimes can be the cause of the onset of neurodegenerative diseases, atherosclerosis, and cancer. These pathologies are characterized by the overexpression of inflammatory markers like endothelial adhesion molecules, such as Vascular Cell Adhesion Molecule-1 (VCAM-1). In the present work, the development of liposomes for therapeutic targeted delivery to inflamed endothelia is described. The idea is to exploit a three-step pretargeting system based on the biotin–avidin high-affinity interaction: the first step involves a previously described biotin derivative bearing a VCAM-1 binding peptide; in the second step, the avidin derivative NeutrAvidinTM, which strongly binds to the biotin moiety, is injected; the final step is the administration of biotinylated liposomes that would bind to NeutravidinTM immobilized onto VCAM-1 overexpressing endothelium. Stealth biotinylated liposomes, prepared via the thin film hydration method followed by extrusion and purification via size exclusion chromatography, have been thoroughly characterized for their chemico-physical and morphological features and loaded with metformin hydrochloride, a potential anti-inflammatory agent. The three-step system, tested in vitro on different cell lines via confocal microscopy, FACS analysis and metformin uptake, has proved its suitability for therapeutic applications.
Quantifying nanoscopic alterations associated with mitochondrial dysfunction using three-dimensional single-molecule localization microscopy

Mitochondrial morphology provides unique insights into their integrity and function. Among fluorescence microscopy techniques, 3D super-resolution microscopy uniquely enables the analysis of mitochondrial morphological features individually. However, there is a lack of tools to extract morphological parameters from super-resolution images of mitochondria. We report a quantitative method to extract mitochondrial morphological metrics, including volume, aspect ratio, and local protein density, from 3D single-molecule localization microscopy images, with single-mitochondrion sensitivity. We validated our approach using simulated ground-truth SMLM images of mitochondria. We further tested our morphological analysis on mitochondria that have been altered functionally and morphologically in controlled manners. This work sets the stage to quantitatively analyze mitochondrial morphological alterations associated with disease progression on an individual basis.
Unveiling Novel Urease Inhibitors for Helicobacter pylori: A Multi-Methodological Approach from Virtual Screening and ADME to Molecular Dynamics Simulations

Helicobacter pylori (Hp) infections pose a global health challenge demanding innovative therapeutic strategies by which to eradicate them. Urease, a key Hp virulence factor hydrolyzes urea, facilitating bacterial survival in the acidic gastric environment. In this study, a multi-methodological approach combining pharmacophore- and structure-based virtual screening, molecular dynamics simulations, and MM-GBSA calculations was employed to identify novel inhibitors for Hp urease (HpU). A refined dataset of 8,271,505 small molecules from the ZINC15 database underwent pharmacokinetic and physicochemical filtering, resulting in 16% of compounds for pharmacophore-based virtual screening. Molecular docking simulations were performed in successive stages, utilizing HTVS, SP, and XP algorithms. Subsequent energetic re-scoring with MM-GBSA identified promising candidates interacting with distinct urease variants. Lys219, a residue critical for urea catalysis at the urease binding site, can manifest in two forms, neutral (LYN) or carbamylated (KCX). Notably, the evaluated molecules demonstrated different interaction and energetic patterns in both protein variants. Further evaluation through ADMET predictions highlighted compounds with favorable pharmacological profiles, leading to the identification of 15 candidates. Molecular dynamics simulations revealed comparable structural stability to the control DJM, with candidates 5, 8 and 12 (CA5, CA8, and CA12, respectively) exhibiting the lowest binding free energies. These inhibitors suggest a chelating capacity that is crucial for urease inhibition. The analysis underscores the potential of CA5, CA8, and CA12 as novel HpU inhibitors. Finally, we compare our candidates with the chemical space of urease inhibitors finding physicochemical similarities with potent agents such as thiourea.
Phenotypic and transcriptional characterization of F. tularensis LVS during transition into a viable but non-culturable state

Francisella tularensis is a gram-negative, intracellular pathogen which can cause serious, potentially fatal, illness in humans. Species of F. tularensis are found across the Northern Hemisphere and can infect a broad range of host species, including humans. Factors affecting the persistence of F. tularensis in the environment and its epidemiology are not well understood, however, the ability of F. tularensis to enter a viable but non-culturable state (VBNC) may be important. A broad range of bacteria, including many pathogens, have been observed to enter the VBNC state in response to stressful environmental conditions, such as nutrient limitation, osmotic or oxidative stress or low temperature. To investigate the transition into the VBNC state for F. tularensis, we analyzed the attenuated live vaccine strain, F. tularensis LVS grown under standard laboratory conditions. We found that F. tularensis LVS rapidly and spontaneously enters a VBNC state in broth culture at 37°C and that this transition coincides with morphological differentiation of the cells. The VBNC bacteria retained an ability to interact with both murine macrophages and human erythrocytes in in vitro assays and were insensitive to treatment with gentamicin. Finally, we present the first transcriptomic analysis of VBNC F. tularensis, which revealed clear differences in gene expression, and we identify sets of differentially regulated genes which are specific to the VBNC state. Identification of these VBNC specific genes will pave the way for future research aimed at dissecting the molecular mechanisms driving entry into the VBNC state.
GO Analysis of GRIN Lens Antennas by Combining in a Single ODE, Field and Wavefront-Curvature Transport to the Ray Tracing

A novel very efficient algorithm based on geometrical optics (GO) is presented for the analysis of graded index (GRIN) lens antennas, namely, dielectric inhomogeneous lenses with a 3-D arbitrary varying refractive index. A family of curved ray paths are traced starting from a set of points defined on the lens input interface, which is illuminated by a feed antenna, up to a corresponding set of points on the output interface, i.e., the lens radiating aperture. The ray tracing is numerically performed in combination with the field transportation along the ray by exploiting an additional wavefront-curvature transport equation, thus providing a single independent vector ordinary differential equation (ODE) for each ray. This scheme allows a complete parallelization of the algorithm by assigning any ray to a different thread. Crossing the lens input–output interfaces at the two end points of the curved ray is accomplished by augmenting the refraction Snell’s law and the Fresnel transmission coefficients with a novel compact closed-form dyadic formula for the transmitted wavefront curvature. The ODE output provides the field aperture distribution on the output lens interface, permitting the far-field calculation as a radiation integral. To this end, an ad hoc quadrature rule is exploited, which requires an aperture sampling rate corresponding to the slowly varying part of the integrand, while the rapid phase variation is accounted for analytically, thus resulting in an extremely efficient and frequency-independent scheme. The effectiveness and accuracy of the algorithm are shown by resorting to a couple of well-known analytical benchmarks and to two more general examples with real-life antennas: a spaceborne weather radar lens antenna and a feed antenna with a zero-focal lens.
Ameliorative Effects of Zingiber officinale Rosc on Antibiotic-Associated Diarrhea and Improvement in Intestinal Function

The global increase in antibiotic consumption is related to increased adverse effects, such as antibiotic-associated diarrhea (AAD). This study investigated the chemical properties of Zingiber officinale Rosc (ZO) extract and its ameliorative effects using a lincomycin-induced AAD mouse model. Intestinal tissues were evaluated for the expression of lysozyme, claudin-1, and α-defensin-1, which are associated with intestinal homeostasis. The cecum was analyzed to assess the concentration of short-chain fatty acids (SCFAs). The chemical properties analysis of ZO extracts revealed the levels of total neutral sugars, acidic sugars, proteins, and polyphenols to be 86.4%, 8.8%, 4.0%, and 0.8%, respectively. Furthermore, the monosaccharide composition of ZO was determined to include glucose (97.3%) and galactose (2.7%). ZO extract administration ameliorated the impact of AAD and associated weight loss, and water intake also returned to normal. Moreover, treatment with ZO extract restored the expression levels of lysozyme, α-defensin-1, and claudin-1 to normal levels. The decreased SCFA levels due to induced AAD showed a return to normal levels. The results indicate that ZO extract improved AAD, strengthened the intestinal barrier, and normalized SCFA levels, showing that ZO extract possesses intestinal-function strengthening effects.
Discovery of Novel Antitumor Small-Molecule Agent with Dual Action of CDK2/p-RB and MDM2/p53

Cell cycle-dependent kinase 2 (CDK2) is located downstream of CDK4/6 in the cell cycle and regulates cell entry into S-phase by binding to Cyclin E and hyper-phosphorylating Rb. Proto-oncogene murine double minute 2 (MDM2) is a key negative regulator of p53, which is highly expressed in tumors and plays an important role in tumorigenesis and progression. In this study, we identified a dual inhibitor of CDK2 and MDM2, III-13, which had good selectivity for inhibiting CDK2 activity and significantly reduced MDM2 expression. In vitro results showed that III-13 inhibited proliferation of a wide range of tumor cells, regardless of whether Cyclin E1 (CCNE1) was overexpressed or not. The results of in vivo experiments showed that III-13 significantly inhibited proliferation of tumor cells and did not affect body weight of mice. The results of the druggability evaluation showed that III-13 was characterized by low bioavailability and poor membrane permeability when orally administered, suggesting the necessity of further structural modifications. Therefore, this study provided a lead compound for antitumor drugs, especially those against CCNE1-amplified tumor proliferation.
High clonality of Mycobacterium avium subsp. paratuberculosis field isolates from red deer revealed by two different methodological approaches of comparative genomic analysis

Mycobacterium avium subsp. paratuberculosis (MAP) is the aetiological agent of paratuberculosis (Johne’s disease) in both domestic and wild ruminants. In the present study, using a whole-genome sequence (WGS) approach, we investigated the genetic diversity of 15 Mycobacterium avium field strains isolated in the last 10 years from red deer inhabiting the Stelvio National Park and affected by paratuberculosis. Combining de novo assembly and a reference-based method, followed by a pangenome analysis, we highlight a very close relationship among 13 MAP field isolates, suggesting that a single infecting event occurred in this population. Moreover, two isolates have been classified as Mycobacterium avium subsp. hominissuis, distinct from the other MAPs under comparison but close to each other. This is the first time that this subspecies has been found in Italy in samples without evident epidemiological correlations, having been isolated in two different locations of the Stelvio National Park and in different years. Our study highlights the importance of a multidisciplinary approach incorporating molecular epidemiology and ecology into traditional infectious disease knowledge in order to investigate the nature of infectious disease in wildlife populations.