Abstract Background Pediatric low-grade gliomas (pLGG) are the most common childhood solid tumors. While typically indolent with excellent prognoses, certain mutations have been associated with aggressive tumor behavior. Case Presentation A 19-month-old with biopsy-confirmed pLGG experienced symptoms and progression of residual tumor two months following debulking surgery. Repeat debulking and biopsies similarly confirmed pLGG, while molecular analyses identified a FGFR1:TACC1 fusion. Discussion While rare, pLGG can exhibit aggressive tumor biology. This review highlights the role of FGFR aberrations in pLGG characterization, prognostication, and clinical decision-making. An examination of targeted therapies and ongoing clinical trials for recalcitrant pLGG was also performed.

Case Report – Vollet Mehdi

This study explores the preparation and optimization of low-strength recycled coarse aggregate concrete using Response Surface Methodology (RSM). With the massive global generation of construction waste, it has become a pressing environmental issue for many countries. Numerous nations are actively seeking ways to recycle construction waste to reduce dependency on natural resources and minimize environmental pollution. In this context, this study begins by testing the basic properties of recycled coarse aggregates derived from construction waste. Through single-factor experiments, the key factors influencing concrete performance and their optimal variation ranges were identified. Subsequently, RSM was employed to optimize the mix design of recycled coarse aggregate concrete, considering the coupling effects between materials. Additionally, by modifying the recycled coarse aggregates, the mechanical properties of the concrete were further enhanced, improving its recyclability. This research provides scientific and technical support for the resourceful utilization of construction waste and the establishment of a closed-loop recycling system.

This study examines the roles of Steam, Metacritic, and Twitch in influencing video game success, integrating data from these platforms to uncover key predictors of revenue. Using machine learning models, the analysis identifies Steam metrics-such as follower counts, peak concurrent users, and total reviews-as the most significant drivers of game revenue, followed by Twitch's viewer engagement. In contrast, Metacritic scores show minimal financial impact. These findings emphasize the importance of leveraging audience data and live-streaming platforms in game marketing. The study provides actionable insights for developers and marketers while highlighting opportunities for future research into cross-platform dynamics and additional performance metrics.

Background: Severe acute respiratory infection (SARI) is an important health issue,which was broadly impacted by COVID-19 pandemic. However, changes of epidemic trends and characteristics involving multiple respiratory pathogens are not well defined.This study aimed to characterize the circulation patterns of common respiratory pathogens before, during, and after the pandemic. Methods: The retrospective observational multi-center study was conducted at seven sentinel hospitals in Shanghai,China from 2019 to 2023. Patients with SARI aged 15 years and older were tested for 12 respiratory pathogens (22 subtypes) using real-time polymerase chain reaction. Results: Of the 4738 patients tested,the positive rate of the pathogens decreased from the pre-pandemic year to the pandemic years by 45.47% (from 30.26% to 16.50%), and then increased by 21.64% (from 16.50% to 20.07%) in the post-pandemic year. The change of each pathogen showed four different patterns: (1) decreased first and then increased (IFV, M. pneumoniae, B. pertussis, HBoV); (2) continuing decreased (HPIV, HCoV, HAdV, EV/HRV, L. pneumophila); (3) increased first and then decreased (HMPV); (4) continuing increased (RSV). Among the three periods, IFV, EV/HRV, and HCoV remained stay on the top five positions of the spectrum, M. pneumoniae was the top pathogen found among 15-44 years of age (33.65%). Varied seasonality was observed among patients with SARI. The co-infection rates of the SARI patients were 1.14% (54/4738), of which mixed infection of IFV and M. pneumoniae was most common (20.37%). Conclusions: Circulation patterns of the common respiratory pathogens changed from 2019 to 2023. It is necessary to be alert to outbreak or epidemic of certain pathogens, as well as strengthening the surveillance for the risk of co-epidemic of multiple respiratory pathogens.

In the past year, the FDA, the EMA or the MHRA authorised fifty-three (53) novel drugs. While this 2024 harvest is not as rich as that of 2023, when 70 new chemical entities were approved, the number of “orphan” drug authorisations in 2024 (21) is similar to that of 2023 (24), illustrating the very dynamic development of therapeutics in areas of high unmet need. Clearly, the most striking characteristic of the 2024 drug yield is the creative pharmacological design, which allows these medicines to employ a novel approach to target a disease. Some such 2024 notable examples are: the first drug successfully using a ”dock-and-block” mechanism of inhibition (zenocutuzumab), the first approved drug for schizophrenia designed as an agonist of M1/M4 muscarinic receptors (xanomeline), the first biparatopic antibody (zanidatamab), binding two distinct epitopes of the same molecule, the first haemophilia therapy that instead of relying on external supplementation of clotting factors, restores Factor Xa activity by inhibiting TFPI (marstacimab), or the first ever authorized direct telomerase inhibitor (imetelstat) that reprogrammes the tumour cells’ oncogenic drive. In addition, in 2024 an impressive percentage of the novel drugs were first-in-class (28 out of 53, or 53% of the total) and a substantial number of them can be considered disease-agnostic, indicating the possibility of future approved extension of their use into additional indications. Overall, the 2024 harvest demonstrates the therapeutic potential of innovative pharmacological design, which allows the effective targeting of intractable disorders and addresses crucial, unmet therapeutic needs

The Gulf of St. Lawrence (GSL) is a semi-enclosed sea located in Atlantic Canada, which is warming rapidly. Redfish, a complex of two morphologically similar, demersal fish species (Sebastes mentella and S. fasciatus), have drastically increased in biomass after two decades of low biomass. Meanwhile, several cold-water species, such as the northern shrimp (Pandalus borealis), are collapsing. The latter is an important prey for redfish and, in addition to a temperature-driven shrinking habitat, they are likely suffering from an increase in predation pressure. To better understand the trophic dynamics between these key species of the GSL, we studied their functional response. Functional responses describe how the rate of consumption of a resource by a consumer changes with the resource’s density, providing precious insights on the energy flow between the two species and the stability of their dynamics. Using Generalized Additive Models, we show that redfish currently exhibit a type III functional response towards northern shrimp, associated with a predation pressure that decreases at low shrimp densities. This type of response is known to have a stabilising effect on population dynamics and might mitigate redfish impact on shrimp populations. Furthermore, this response evolved between the 1990s and the 2010s, suggesting a possible adaptation of redfish to their changing environment. Our models also showed significant negative effects of warming environmental conditions as well as trophic competition on shrimp consumption by redfish and confirmed the importance of predator size on their feeding habits, as observed in previous studies.

Central nervous system (CNS) involvement in acute lymphoblastic leukaemia is associated with a poor prognosis, making accurate detection essential for risk stratification and guiding treatment decisions. Cytomorphology of cerebrospinal fluid has been the gold standard for assessing CNS involvement. However, it has limited sensitivity, particularly in low cell counts. Flow cytometry has emerged to be a valuable diagnostic tool with higher sensitivity, particularly in paucicellular samples. Occult CNS disease has emerged as a newer group where the cytomorphology shows no blasts while the flowcytometry records the leukemic blast population. Flow cytometry remains challenging due to the lack of standardised positivity criteria, unclear prognostic implications and management strategies for occult CNS diseases. This systematic review critically examines the methodologies for detecting leukemic infiltration within cerebrospinal fluid, focusing on conventional cytomorphology and multiparameter flow cytometry. In addition, it also addresses key pre-analytical variables, such as cerebrospinal fluid volume, processing time, and total nucleated cell counts. These parameters significantly influence the accuracy of both methods. Future research is required to establish uniform diagnostic guidelines and assess the clinical relevance of occult CNS disease in acute lymphoblastic leukaemia.

In addition to improving coffee quality, producing coffee under various shade tree species is essential for maintaining and reviving agroecology and nature-based agroforestry techniques. The study was carried out in Ethiopia’s Oromia regional states in the Jimma Zone’s Chora Botor district (Chalalaki coffee plantation). The experiment was overlaid on coffee farm that has been established by using four released Arabica coffee varieties (7440,744, F59, and 75227) under three suggested coffee shade trees (Albizia gummifera, Millettia feruginea, and Acacia abyssinica). To evaluate the effect of shade tree species and coffee varieties on quality of coffee data on raw, organoleptic and biochemical traits were collected and analyzed using split plot design with three replications. The study’s findings demonstrated that, hundred bean weight (HBW) was only influenced by coffee varieties but not by shade tree species. On the other hand, coffee varieties and shade tree species had a substantial impact on raw quality (primary and secondary defects apart from odor), organoleptic quality (cup cleanness, acidity, body and flavor) and biochemical quality (caffein, total chlorogenic acid and trigonelline). Acacia abyssinica, and Albizia gummifera, are prominent shade tree species that improve the quality of coffee due to its contribution in soil organic matter build up through litter fall and, root decomposition, and slowdown of the rate of ripening of coffee cherries. This enhanced the development of beneficial compounds that improve the raw, organoleptic and biochemical qualities of coffee. The delayed ripening process of coffee under shade lead to higher quality coffee beans with desirable flavor Hence, choosing the right combination of coffee varieties and shade tree species is very crucial for improving coffee bean quality and sustainable production of coffee in coffee-based farming system of southwest Ethiopia.

The typification of the names A. micrantha, A. donaciformis, A. formosana, A. formosana var. gracilis (currently A. formosana subsp. gracilis), A. parviflora (a heterotypic synonym of A. formosana), A. bifaria, and A. donax var. coleotricha (these two as heterotypic synonyms of A. donax) is discussed. The “types” of these names were previously indicated as “holotypes” in 2012 and 2017. However, the type indication was ineffective in all cases according to the International Code of Nomenclature for algae, fungi, and plants (ICN, Shenzhen Code of 2018). We proposes here the effective lectotypification of these five names, along with data on the gatherings and syntypes used to describe these taxa. The name A. micrantha is lectotypified using a specimen collected by Desfontaines and preserved at P. The lectotype of A. donaciformis is selected from a specimen collected by Jean Honoré Perreymond in southern France and kept at AV (Muséum Requien). Arundo formosana and A. formosana var. gracilis are typified from original specimens preserved in the Hackel Herbarium at W. The lectotype of the name A. parviflora is designated from a specimen preserved at US. Finally, a second-step lectotypification is made for the name A. bifaria with the lectotype preserved at LD, and the lectotype of A. donax var. coleotricha is selected from a specimen preserved at W

A document by Xavier Pardell Peña. Click on the document to view its contents.

Context- Implementation of a new digital platform using google sites, google suites, in educational practices for eLearning in a regular classroom setting, the context of this study will be the starting point in order to address this problem

A document by Ali Asl Sharhani. Click on the document to view its contents.

Medical images aid in disease diagnosis, but manual analysis is time-consuming. To streamline this, a Vision Transformer-based framework is used for automatic multi-class image classification, addressing limited datasets and static Deep Learning frameworks. The COVID-19 CXR data set, the ARS-COV-2 CXR data set, and the COVID-19 Posterior-Anterior Chest Radiography (X-rays) data set has been used for training, validation, and testing processes. The training image data has been divided into flattened regions known as Visual Tokens. The transformer encoder has been then fed the flattened regions of the input image. With its positional encoding, the transformer encoder creates visual tokens of the input image. The encoded visual tokens have been then delivered to MLP, which is followed by a soft-max algorithm to categorize the images. Experimental results have shown that the overall accuracy of the vision transformer-based detection model is 0.7346 with precision 0.6997, Sensitivity 0.7318, and F1-Score 0.7126.

Bats are capable of highly dexterous flight maneuvers that rely heavily on highly articulated hand skeletons and malleable wing membranes. To understand the underlying mechanisms, large amounts of detailed data on bat flight kinematics are required. Conventional methods to obtain these data have been based on tracing landmarks and require substantial manual efforts. To generate 3D reconstructions of the entire geometry of a flying bat in a fully automated fashion, the current work has developed an approach where the pose of a trainable articulated mesh template that is based on the bat’s anatomy is optimized to fit a set of binary silhouette representing views from different directions of the flying bat. This is followed by post-processing to smooth the reconstructed kinematics and simulate the non-rigid motion of the wing membranes. To evaluate the method, 10 flight sequences that represent several flight maneuvers (e.g., straight flight, takeoff, u-turn) and were recorded in a flight tunnel instrumented with 50 synchronized cameras have been reconstructed. A total of 4,975 reconstructions are generated in this fashion and subject to qualitative and quantitative evaluations with promising results. The reconstructions are to be used for quantitative analyses of the maneuvering kinematics and the associated aerodynamics.

Objective: To identify predictive factors for intrapartum cesarean section (CS) in grand multiparous women and compare them with primiparous and multiparous women. Design and Setting: A historical cohort study in a single university-affiliated tertiary medical center. Population: All women with singleton pregnancies resulted in live births (n = 74,848) between 2011-2018. Women were categorized into three groups: primiparous (PP, first birth), multiparous (MP, 2–4 births), and grand multiparous (GMP, ≥5 births). Methods: We analyzed delivery characteristics and indications for intrapartum emergency CS. We then used multivariate logistic regression to identify factors associated with an increased risk of emergency CS. Main Outcome Measures: Proportion of intrapartum CS and its indications among the parity groups. Results: Intrapartum CS rates were significantly higher in the PP group (13.2%) compared to MP (9.4%) and GMP + GGMP (6.5%) (p <.001). Non-reassuring fetal heart rate (NRFHR) was the leading indication for intrapartum CS in GMP women (71.1%), followed by failure to progress (21.0%), suspected placental abruption (4.4%), suspected uterine rupture (2.6%), and failed instrumental delivery (0.9%). Multivariate analysis identified the following factors as significantly associated with increased risk of emergency CS: assisted reproductive technology (aOR = 2.09, 95% CI 1.88–2.32), prolonged latency >12 hours post-rupture of membranes (aOR = 2.08, 95% CI 1.85–2.34), tobacco use (aOR = 1.49, 95% CI 1.26–1.75), and diabetes (aOR = 1.46, 95% CI 1.32–1.62). Conclusions: Grand multiparous women had a lower risk for intrapartum CS compared to primiparous and multiparous women. Non-reassuring fetal heart rate was the most common indication for emergency CS. Assisted reproductive technology (ART), prolonged rupture of membranes (ROM) latency, tobacco use, and diabetes were independent predictors of intrapartum CS.

Objective: The Personality Inventory for DSM-5 (PID-5) is the primary operationalization of the DSM-5 AMPD maladaptive trait framework. This study sought to examine the temporal stability of the PID-5 across one-year, as well as its concurrent and longitudinal associations with clinically relevant external criteria. Methods: Participants with heighted borderline personality features completed the PID-5 and measures of emotional, cognitive, and behavioral processes, as well as psychiatric symptomology, at baseline ( N = 107) and 1-year follow-up ( N = 72). Rank-order stability and mean-level changes for the PID-5 domains and facets were calculated, along with correlations with outcomes. Results: Results suggest high stability in terms of rank-order (median test-retest reliability estimate of .74 for domains and .70 for facets), but small to moderate mean-level changes were common. Prospective associations with clinical criteria suggest domains and facets are predictive of important therapeutic change processes and outcomes in theoretically expected ways. Conclusion: Findings generally support the stability of AMPD maladaptive traits and provide further evidence for the model’s clinical utility.

CHAPTER 5 — Transfer Learning for NLP TasksDOI Linked to Final Edition PreprintDOI: 10.22541/au.173627634.41673828/v1Status: Archived pre-publication draft (2025) — SupersededThis chapter is an early developmental version later finalized and published as part of:Leocadio, Paulo H. (2025). Mastering NLP with Hugging Face: Leveraging diffusion models, transformers, and reinforcement learning for generative and analytical systems. . BPB Publications — ISBN: 978-9365893182 (Released February 28, 2026).A significantly updated, expanded, and editorially refined version appears in the published edition. This preprint is preserved for scholarly transparency, version tracking, and citation continuity.For academic use:        • Cite this DOI as the preprint record, or        • Cite the published book for the authoritative edition.Readers seeking the most accurate and up-to-date content should refer to the published version

We herein report a woman in her 70s was admitted to hospital with myocardial and multiple lacunar cerebral infarction, transthoracic echocardiogram revealed an active thrombus in the left atrium like a ping-pong ball. Anticoagulation was administered with low molecular weight heparin but did not work, the patient later developed cerebral infarction in the right frontotemporal lobe. There is a greater risk of severe cerebral infarction in active left atrial thrombus without mitral stenosis. Echocardiography played an important role in definitive diagnosis.

In the field of mobile IoT systems, particularly the adaptability and performance of mobility models play a critical role in optimizing RPL, an essential aspect in acquiring reliable and efficient communication in resource-constrained and dynamic environments. RPL, developed for certain static sensor networks, suffered various challenges in mobile landscapes where node mobility affects energy efficiency, reliability, and network performance. Therefore, this survey seeks to compare and review several mobility models, including the RPGM, MMM, GMM, MRW, RDM, RWM, and RWP, to address such challenges. The research facilitates a comprehensive examination of the applicability, disadvantages, advantages, and characteristics of all mobility models in promoting the role of RPL-focused mobile IoT systems. The study focuses on the effects of node mobility on routing stability, network throughput, and energy consumption, identifying key factors influencing protocol adaptation in dynamic environments. Experimental methodologies are employed to assess RPL's performance under these models, and the results are critically compared to highlight the strengths and limitations of different mobility models in supporting mobile IoT networks. The findings underscore the importance of selecting appropriate mobility models for optimizing RPL performance, particularly in scenarios involving mobile nodes such as vehicular networks, smart cities, and emergency response systems. The paper concludes by suggesting future research directions, including protocol enhancements, hybrid mobility models, and the integration of artificial intelligence for more adaptive routing solutions in mobile IoT environments.

[Abstract]This paper presents the direct field oriented control (FOC) for an induction motor (IM) with a nonlinear controller based on the technique of an input output feedback linearization control, that allows us to control the speed and the rotor flux using two cascade controller one for the stator currents and the other one for the speed and rotor flux.Where we associated those controllers with an adaptive nonlinear observer that estimate the currents and the parameters ( K T r ) and K for the first controller ,and since the second one contains the load torque as an input and since its unmeasured then a second order Leuenberger observer is used to compensate it that uses the speed as a measured state stator currents as an input vector.Where the proposed controller and observers shows a perfect speed and rotor flux tracking even in the presence of parameter uncertainties as well as a perfect parameter and load torque estimation ,hence simulation results have been performed under Matlab/Simulink that shows their performance.

This study examines the impact of elevated temperatures on the mechanical properties of Borassus husk fibre-reinforced epoxy composites, focusing on the effects of alkali treatment (5% NaOH) on the fibres with varying treatment durations. Dynamic Mechanical Analysis (DMA) was conducted according to ASTM 5418-01 standards. The results showed that both untreated and alkali-treated fibres increased the storage modulus of the composites. The loss modulus significantly increased only for the alkali-treated composites, where the 1-hr treated fibre composite show the highest value. The glass transition temperature (Tg) of neat epoxy was 82 °C, which increased to 89 °C for composites with 0.75-hr treated fibres but decreased to 79 °C for untreated fibres. The tan δ (damping factor) also increased significantly with alkali treatment, with the highest value (1.2) observed for the 0.75-hr treated fibre composite, 33% higher than neat epoxy (0.9). Cole-Cole plots revealed improved resin-fibre adhesion for composites incorporated with 0.75 and 1 hour treated husk fibre. Phase angle data confirmed enhanced energy dissipation and viscoelastic properties in the treated fibre/epoxy composites. Furthermore, the total mass loss (TML) was the lowest for the 0.75-hr treated fibre/epoxy composite (0.4%), about 33% lower than neat epoxy, indicating better thermo-mechanical stability. Overall, alkali-treated Borassus husk fibre composites demonstrated superior mechanical stiffness, damping capacity and thermal stability compared to neat epoxy, making them promising materials for applications in aerospace and automotive industries, where performance, vibration reduction and sustainability are essential.

The recent study was to investigate the synergistic activity of Chitosan, Alum, and PVA cross-linked haemostatic film to stop bleeding during the war and other accidental causes. In India around 30- 40% of uncontrolled haemorrhage responsible for trauma-related death. Formulation of haemostatic patches was done by solvent casting method. The physicochemical property of the film was assessed, and the result was found satisfactory. Effective results showed that the platelet count and blood-clotting index (BCI) were achieved in vitro by Chitosan composite alum (CH- alum) haemostatic film. Moreover, CH- alum haemostatics film had the best haemostatics effect in rat liver laceration model tests, rat jugular vein, and rat femoral artery model compared to with Chitosan (CH) and Alum haemostatics film. In conclusion, the formulation and development of chitosan- alum haemostatics film can be used as good haemostatics material in the treatment of blood loss. The haemostatics film has also anti microbial activity which is very important for wound healing. It helps to reduce the microbial growth on wound. Chitosan also has anti microbial effect shown in various study.

The development of broad-spectrum universal influenza vaccines and optimisation of vaccination strategies to address the threats posed by pandemics and emerging influenza viruses are critical for public health. In this study, an adenovirus type 5 vector-based influenza vaccine carrying the hemagglutinin (HA) stem of H1, HA stem of H3, and neuraminidase of N1 from the influenza virus was constructed. Immune responses were evaluated in mice using various vaccination strategies: prime-only (intramuscular [IM] or intranasal [IN]) and prime-boost (IM+IN). Compared to the prime-only strategy, the prime-boost strategy significantly enhanced the systemic immune response, inducing higher levels of antigen-specific IgG, mucosal IgA, and T cell immunity in the spleen and lungs. Furthermore, the IN boosting strategy provided complete protection in mice challenged with the H1N1-PR8, rgH3N2-X31, and rgH5N1-Vietnam viruses, significantly reducing viral loads in the lungs and alleviating lung tissue pathologies. In conclusion, this study elucidates potential avenues for the development and application of universal influenza vaccines using customised mucosal boosting strategies.