Miracle-dz/UniFAR-FTUs huggingface dataset:
A GRU-based traffic situation prediction method in multi-domain software defined network

With the continuous development and improvement of Software-Defined Networking (SDN), large-scale networks are divided into multiple domains. Each domain, which is managed by a controller, forms multi-domain SDN architecture. In multi-domain SDN, the dynamics and complexity are more significant, bringing great challenges to network management. Comprehensively and accurately predicting traffic situation in multi-domain SDN can better maintain network stability. In this article, we propose a traffic situation prediction method based on the gated recurrent unit (GRU) network in multi-domain SDN. We first analyzed the relevant factors that affect data traffic and control traffic and transformed them into a time series of actual situation values. Then, to enhance the prediction performance of GRU, we used the salp swarm algorithm to optimize the hyperparameters of GRU automatically. Finally, we adopted hyperparameter optimized GRU to achieve traffic situation prediction in multi-domain SDN. The experimental results indicate that the proposed method outperforms other traditional machine learning algorithms in terms of prediction accuracy.
Evaluation of the antimicrobial and antibiofilm activity of sweet cherry (Prunus avium L.) stems extracts

Sweet cherry (Prunus avium L.) stems in the form of infusions and decoctions are traditionally consumed for diuretic and anti-inflammatory purposes. This study aimed to evaluate antimicrobial and antibiofilm activity of ethanolic and methanolic extract made from sweet cherry stems. Extracts are obtained by the Soxhlet extraction and maceration procedures. For the determination of the minimum inhibitory concentration, the broth microdilution method is employed, and the assessment of the microbiocidal activity of the extracts is conducted. The antibiofilm activity was tested through the tissue culture plate method, which also allowed the determination of the biofilm-forming categories of investigated strains. The final step involved the calculation of the biofilm inhibition percentage. Examined extracts with the balanced activity inhibited the growth of all microorganisms, with Gram-negative bacteria being more sensitive in comparison to Gram-positive. The values of the minimum inhibitory concentration were 125 µg/ml, and 250 µg/ml, respectfully. Candida albicans was the most susceptible and the minimum inhibitory concentration of both extracts was 62.50 µg/ml. The microbiocidal activity of the extracts was not recorded. Extracts exhibited different impacts on the biofilm-forming capacity of the investigated microbes, and both inhibition and stimulation effects are noted. The percentage of the biofilm inhibition was from 14.27% to 84.78%, with the highest inhibition recorded for the multidrug-resistant Escherichia coli, treated with the ethanolic extract. Sweet cherry stems are a valuable source of natural bioactive compounds, but their usage in the treatment of microbial infections should be correctly and carefully implemented.
Altered Coupling Between Cerebral Blood Flow and Voxel-Mirrored Homotopic Connectivity Affects Stroke-Induced Speech Comprehension Deficits

The neurophysiological basis of the association between interhemispheric connectivity and speech comprehension processing remains unclear. This prospective study examined regional cerebral blood flow (CBF), homotopic functional connectivity, and neurovascular coupling, and their effects on comprehension performance in post-stroke aphasia. Multimodal imaging data (including data from functional magnetic resonance imaging and arterial spin labeling imaging) of 19 patients with post-stroke aphasia and 22 healthy volunteers were collected. CBF, voxel-mirrored homotopic connectivity (VMHC), CBF-VMHC correlation, and CBF/VMHC ratio maps were calculated. Between-group comparisons were performed to identify neurovascular changes, and correlation analyses were conducted to examine their relationship with the comprehension domain. The correlation between CBF and VMHC of the global gray matter decreased in patients with post-stroke aphasia. The total speech comprehension score was significantly associated with VMHC in the peri-Wernicke area [posterior superior temporal sulcus (pSTS): r = 0.748, p = 0.001; rostroventral area 39: r = 0.641, p = 0.008]. The decreased CBF/VMHC ratio was also mainly associated with the peri-Wernicke temporoparietal areas. Additionally, a negative relationship between the mean CBF/VMHC ratio of the cingulate gyrus subregion and sentence-level comprehension was observed (r = −0.658, p = 0.006). These findings indicate the contribution of peri-Wernicke homotopic functional connectivity to speech comprehension and reveal that abnormal neurovascular coupling of the cingulate gyrus subregion may underly comprehension deficits in patients with post-stroke aphasia.
Improving Traffic Load Distribution Fairness in Mobile Social Networks

Mobile social networks suffer from an unbalanced traffic load distribution due to the heterogeneity in mobility of nodes (humans) in the network. A few nodes in these networks are highly mobile, and the proposed social-based routing algorithms are likely to choose these most “social” nodes as the best message relays. Finally, this could lead to inequitable traffic load distribution and resource utilisation, such as faster battery drain and/or storage consumption of the most (socially) popular nodes. We propose a framework called Traffic Load Distribution Aware (TraLDA) to improve traffic load balancing across network nodes. We present a novel method for calculating node popularity which takes into account both node inherent and social-relations popularity. The former is purely determined by the node’s sociability level in the network, and in TraLDA is computed using the Kalman prediction which considers the node’s periodicity behaviour. However, the latter takes the benefit of interactions with more popular neighbours (acquaintances) to boost the popularity of lower (social) level nodes. Using extensive simulations in the Opportunistic Network Environment (ONE) driven by real human mobility scenarios, we show that our proposed strategy enhances the traffic load distribution fairness of the classical, yet popular social-aware routing algorithms BubbleRap and SimBet without negatively impacting the overall delivery performance.
Description of a novel technique for ultrasound-based planning for gynaecological 3D brachytherapy and comparison between plans of this technique and 2D with fluoroscopy

With the purpose of implementing a way to obtain volumes from ultrasound axial images, a novel method for 3D gynaecologic brachytherapy was assessed, with a 3D-printed attachment for a commercial stepper (for prostate brachytherapy). It allowed the acquisition of a transabdominal axial image series by ultrasound; these images were uploaded to a treatment planning system where high-risk clinical tumour volume (HR-CTV) and risk organs were contoured. A dose administration plan was developed with orthogonal X-ray images (0° and 270° incidences), using International Commission on Radiation Units and Measurements (ICRU) 38 points. The same plan was applied in the ultrasound images’ sequence and their respective volumes; differences were noted. In the 20 cases analysed, with a given point A dose, its corresponding dose delivered to 90% of HR-CTV percentage was highly variable (mean = 104.2, SD = 26.01). There is a significant variation of this percentage when point A falls outside the HR-CTV than when it falls inside ( p < 0.00001). There is a significant correlation in terms of the bladder point dose ICRU 38 and the Maximum dose to 2cc of organ or target volume (D2cc) bladder ( p = 0.021); however, there is no such correlation when we relate the rectum point dose ICRU 38 to the D2cc rectum ( p = 0.327). There was a negative correlation between HR-CTV and D2cc bladder and D2cc rectum; both were statistically significant. There were significant differences comparing ICRU points and dose to prescription and organ at risk volumes, pointing out that there is room for optimisation of plans using the latter technique. So, it is proposed to further test this image modality and compare it to other imaging techniques that allow the creation of volumes, such as computed tomography or magnetic resonance imaging.
Stem Cells and Repair of Myocardial Contraction Bone Marrow Mononuclear Cells

Heart insufficiency remains the leading cause of death despite pharmacological and interventional therapy as well as primary and secondary prevention. Laboratory research on cardiac repair implementing stem cells and progenitor cells has raised great expectations as well as controversies. The potential of diverse progenitor cells to repair damaged heart tissue includes replacement (tissue transplant), restoration (activation of resident cardiac progenitor cells, paracrine effects), and regeneration (stem cell engraftment forming new myocytes). Based on promising experimental results clinical trials including several hundreds of patients with ischemic heart disease have been initiated using mostly bone marrow-derived cells. Probably, due to a lack of standardization of cell isolation and delivery methods these trials showed controverse results regarding effectiveness. However, significant therapeutic regeneration of human myocardium could not be proven until now. Several issues are at debate concerning the translation of the experimental data into the clinic discussing the adequate cell type, dosing, timing, and delivery mode of myocardial stem cell therapy. This review focusses on the potential and clinical translation of cell based therapies in cardiovascular disease.
Deep Camera Obscura: An Image Restoration Pipeline for Lensless Pinhole Photography

Modern machine learning has enhanced the image quality for consumer and mobile photography through low-light denoising, high dynamic range (HDR) imaging, and improved demosaicing among other applications. While most of these advances have been made for normal lens-based cameras, there has been an emerging body of research for improved photography for lensless cameras using thin optics such as amplitude or phase masks, diffraction gratings, or diffusion layers. These lensless cameras are suited for size and cost-constrained applications such as tiny robotics and microscopy that prohibit the use of a large lens. However, the earliest and simplest camera design, the camera obscura or pinhole camera, has been relatively overlooked for machine learning pipelines with minimal research on enhancing pinhole camera images for everyday photography applications. In this paper, we develop an image restoration pipeline of the pinhole system to enhance the pinhole image quality through joint denoising and deblurring. Our pipeline integrates optics-based filtering and reblur losses for reconstructing high resolution still images (2600 × 1952) as well as temporal consistency for video reconstruction to enable practical exposure times (30 FPS) for high resolution video (1920 × 1080). We demonstrate high 2D image quality on real pinhole images that is on-par or slightly improved compared to other lensless cameras. This work opens up the potential of pinhole cameras to be used for photography in size-limited devices such as smartphones in the future.
Invariant-based World Models for Robust Robotic Systems Demonstrated on an Autonomous Football Table

This work explains the use of invariants in robotic perception and control skills. An “invariant” is a mathematical constraint that remains unchanged under a particular transformation in a system. This property makes robotic functionalities more robust against “disturbances” that cause these transformation. These invariants are stored in a world model (WM), which has a central role in the information architecture of the robot to share information between components. A “robotic” football table serves as an example to illustrate the effectiveness of invariants. Despite looking different, all standard football tables satisfy the same set of invariants; the common layout of the field, line markings and puppets, which are not identical but satisfy the same set of constraints, such as parallelism, partial ordering, and relative colour and intensity differences between objects. During initialization, the invariants are actively identified and saved to the world model. During game play this world model is used by the perception and action skills and is updated when necessary. This work shows how the use of invariants creates robustness against variation in placement of the perception system and against variation in table dimensions and colours. When the camera is misaligned or moved mid-play, the world model is updated to ensure a smooth continuation of the game. The approach is tested on three standard football tables, with different dimensions and colours, showing that the approach is robust on standard tables that adhere to the invariants.
Learning Theory-Driven Tips for Designing Effective Learning Solutions for the Continuous Education of Community Pharmacists to Enhance Patient-Centered Care—A Qualitative Study

The constant development of medical and pharmaceutical sciences and the changing roles of pharmacists highlight the importance of lifelong learning in their profession. Given the identified knowledge gaps in the literature in terms of pharmacists’ preferences for lifelong learning, the study aimed to evaluate the opinions and attitudes of community pharmacists towards lifelong learning, including their previous experiences and educational needs, in order to propose evidence-based tips for designing such solutions and interventions intended for them both in face-to-face and online forms. For this purpose, ten semi-structured in-depth interviews were conducted with Polish community pharmacists on the topic using a thematic guide. Subsequently, they were subjected to literal transcription and interpretative phenomenological analysis by two independent researchers using phenomenology as the qualitative approach. The identified themes covered the topic’s relevance for pharmacists’ work, practice-oriented form and content, previous learners’ experiences as a foundation for further learning, commercial initiatives’ risks, motivation sources, and barriers for participation in lifelong learning solutions so far. Based on the insights provided by the respondents, as well as scientifically proven learning theories and educational principles, ten tips were formulated for designing recipient-friendly learning solutions and interventions within the framework of postgraduate lifelong learning of pharmacists.
The Road to HTLV-1-Induced Leukemia by Following the Subcellular Localization of HTLV-1-Encoded HBZ Protein

Human T cell leukemia virus-1 (HTLV-1) is the causative agent of a severe cancer of the lymphoid lineage that develops in 3-5% of infected individuals after many years. HTLV-1 infection may also induce a serious inflammatory pathology of the nervous system designated HTLV-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Two virus-encoded proteins, the viral transactivator Tax-1 and the HTLV-1 basic leucine-zipper factor HBZ, are strongly involved in the oncogenic process. Tax-1 is involved in initial phases of the oncogenic process. Conversely, HBZ seems to be involved in maintenance of the neoplastic state as witnessed by the generation of leukemic/lymphomatous phenotype in HBZ transgenic mice and the persistent expression of HBZ in all phases of the oncogenic process. Nevertheless, the intimate molecular and cellular mechanism mediated by the two viral proteins, particularly HBZ, in oncogenesis still remain elusive. An important step toward the complete comprehension of HBZ-associated oncogenicity is the clarification of the anatomical correlates of HBZ during the various phases of HTLV-1 infection to development of HTLV-1-associated inflammatory pathology and ultimately to the establishment of leukemia. In this review, I will summarize recent studies that have established for the first time a temporal and unidirectional expression of HBZ, beginning with an exclusive cytoplasmic localization in infected asymptomatic individuals and in HAM/TSP patients and ending to a progressive cytoplasmic-to-nuclear transition in leukemic cells. These results are framed within the present knowledge of HTLV-1 infection and the future lines of research that may shed new light on the complex mechanism of HTLV-1- mediated oncogenesis.
Connectivity Restoration of Urban Road Networks With Multivehicle Systems: A Reinforcement Learning Approach

The connectivity of urban road networks plays an important role in ensuring the functions of the infrastructure and the transportation of emergency supplies of a postdisaster city. When a disaster happens, clearing vehicles that are able to open blocked roads are precious resources in connectivity restoration and their work should be planned systematically and promptly. In this article, we proposed a novel reinforcement learning approach to swiftly providing restoration plans for clearing vehicles according to damage situations. This is a cluster-first, route-second type of method that includes an event-triggering algorithm to deal with the time-space model of vehicles and a specially designed cognitive module to decide the vehicle behaviors, which is represented by three kinds of preference in the behavior probability: the guidance, the memory, and the rules. Our approach has been tested on damaged Istanbul and synthetic road networks, confirming its superior capacity to generate near-optimal solutions in an extraordinarily short time, which is more practical and efficient in dealing with the case of multivehicle systems operating on complex large-scale urban road networks.
Symbiotic Modulation as a Driver of Niche Expansion of Coastal Plants in the San Juan Archipelago of Washington State

Modern evolutionary theory and population genetics posit that adaptation and habitat expansion of plants result from processes exclusive to their genomes. Here, we present studies showing that plants can grow across complex habitat gradients by modulating symbiotic associations with Class 2 fungal endophytes. Endophyte analysis of three native (Leymus mollis, Distichlis spicata, and Salicornia pacifica) and one invasive (Spartina anglica) plant growing across adjacent microhabitats in the San Juan Archipelago altered associations with Class 2 fungal endophytes in response to soil salinity levels. At the microhabitat interfaces where the gradation of salinity varied, the plants were colonized by endophytes from both microhabitats. A reciprocal transplant study along a salt gradient demonstrated that Leymus mollis (dunegrass) required endophytes indigenous to each microhabitat for optimal fitness and/or survival. In contrast, when dunegrass and Grindelia integrifolia (gumweed) were found growing in low salinity, but high drought habitats, these plant species had their own unique dominant endophyte association regardless of geographic proximity and conferred drought but not high salt stress tolerance. Modulation of endophyte abundance occurred in planta based on the ability of the symbiont to confer tolerance to the stress imposed on plants. The ability of an endophyte to confer appropriate stress tolerance resulted in a significant increase of in planta fungal abundance. Conversely, the inability of an endophyte to confer stress tolerance resulted in a decrease of in planta fungal abundance. Our studies indicate that Class 2 fungal endophytes can provide a symbiotic mechanism for niche expansion and phenotypic plasticity across environmental gradients.
Análise do ângulo de fase como marcador prognóstico em pacientes críticos cirúrgicos oncológicos

Introdução: Identificar pacientes oncológicos em pós operatório com risco nutricional em unidades de terapia intensiva (UTI) é de suma importância para a prática da terapia nutricional. O ângulo de fase (AF) e o cálculo do Ângulo de fase padronizado (AFP), podem ter valor prognóstico no paciente grave. O objetivo é avaliar o AF assim como a situação nutricional dos pacientes utilizando métodos de antropometria objetiva e de avaliação sistêmica e nutricional para compará-los como preditores de morbidade e mortalidade. Método: Estudo prospectivo, em adultos com câncer submetidos à cirurgia eletiva, admitidos na UTI no pós-operatório imediato. Foram submetidos à avaliação do estado nutricional, impedância bioelétrica (BIA) para obtenção do AF/AFP em até 48h após admissão na UTI e avaliação dos desfechos clínicos em até 28 dias. Os dados foram submetidos à análise estatística, sendo considerado o nível de significância de p <0,05. Resultados: Foram avaliados 51 pacientes, média de idade de 64±11anos. A média do tempo de internação foi de 9±8 dias, sendo o tempo de permanência na UTI de 1±1 dia. Os valores médios de AF foram 4,48º±1,29º e AFP -1,93º±1,35º. A média de AF e AFP foram significativamente menores entre o grupo que evoluiu a óbito 2,97º e -2,95º respectivamente do que naqueles que sobreviveram com resultados de AF e AFP 4,57º e -1,87º respectivamente. A taxa de mortalidade foi de 5,9% (n= 3) no final do período do estudo. Conclusões: Observou-se que os valores de AF e AFP de risco foram menores nos pacientes em risco nutricional, assim como foram identificados menores valores de AF e AFP no grupo que evoluiu a óbito, ressaltando a hipótese que uma redução nos valores de AF e AFP associou-se à piores indicadores clínicos e prognósticos.
Integrated Slow-Light Enhanced Silicon Photonic Modulators for RF Photonic Links

An integrated RF-photonic link that consists of a slow-light enhanced silicon (Si) electro-optic modulator, a single mode Si optical waveguide and a silicon-germanium (SiGe) photodetector was fabricated using a Si photonic standard foundry service. The third-order intermodulation distortion (IMD3) of the RF signals and the link spur-free dynamic range (SFDR) were characterized through a two-tone test method. The Si Mach-Zehnder modulator architecture is designed to have unequal arms to operate on a simplified driving scheme. As a result, on-chip thermal heaters can be omitted, and the modulator can configure near its quadrature point by adjusting the wavelength to the modulator. Owning to enhanced light-matter interaction in the slow-light region, an increased slope efficiency is observed in the modulator. By selecting the optimal DC bias to the grating and the reference arms of the modulator, a SFDR of 96 dB/Hz2/3 can be obtained in the RF link at the slow light region. The slow-light modulator also displays increased modulation efficiency, allowing for a reduced footprint for large array integration.