126 research outputs found

    Auxin pretreatment promotes regeneration of sugarcane (Saccharum spp. hybrids) midrib segment explants

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    We have developed a new, simple, quick and genotype-independent method for direct regeneration of sugarcane using novel midrib segment explants. Our protocol involves two steps: the pretreatment of starting material on MS (Murashige and Skoog (1962) Physiol Plant 15:473–497) medium containing 3.0 mg/l 2,4- dichlorophenoxyacetic acid (2,4-D) for 8 days under continuous dark and subsequent transfer of the explants to MS medium augmented with 0.1 mg/l benzyladenine (BA) and 0.1 mg/l naphthaleneacetic acid (NAA) under light-dark conditions. On the regeneration medium, numerous globular structures appeared from the explants and subsequently differentiated into shoots. Regenerated shoots attained 2–5 cm height within 30 days of culture initiation and readily rooted on MS basal medium. Hardened plants were successfully established in the greenhouse. The regulation of sugarcane morphogenesis by auxin pretreatment is discussed

    Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

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    Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

    Learning curves of basic laparoscopic psychomotor skills in SINERGIA VR simulator

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    Purpose: Surgical simulators are currently essential within any laparoscopic training program because they provide a low-stakes, reproducible and reliable environment to acquire basic skills. The purpose of this study is to determine the training learning curve based on different metrics corresponding to five tasks included in SINERGIA laparoscopic virtual reality simulator. Methods: Thirty medical students without surgical experience participated in the study. Five tasks of SINERGIA were included: Coordination, Navigation, Navigation and touch, Accurate grasping and Coordinated pulling. Each participant was trained in SINERGIA. This training consisted of eight sessions (R1–R8) of the five mentioned tasks and was carried out in two consecutive days with four sessions per day. A statistical analysis was made, and the results of R1, R4 and R8 were pair-wise compared with Wilcoxon signed-rank test. Significance is considered at P value <0.005. Results: In total, 84.38% of the metrics provided by SINERGIA and included in this study show significant differences when comparing R1 and R8. Metrics are mostly improved in the first session of training (75.00% when R1 and R4 are compared vs. 37.50% when R4 and R8 are compared). In tasks Coordination and Navigation and touch, all metrics are improved. On the other hand, Navigation just improves 60% of the analyzed metrics. Most learning curves show an improvement with better results in the fulfillment of the different tasks. Conclusions: Learning curves of metrics that assess the basic psychomotor laparoscopic skills acquired in SINERGIA virtual reality simulator show a faster learning rate during the first part of the training. Nevertheless, eight repetitions of the tasks are not enough to acquire all psychomotor skills that can be trained in SINERGIA. Therefore, and based on these results together with previous works, SINERGIA could be used as training tool with a properly designed training program

    Cerebral microbleeds and intracranial haemorrhage risk in patients anticoagulated for atrial fibrillation after acute ischaemic stroke or transient ischaemic attack (CROMIS-2):a multicentre observational cohort study

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    Background: Cerebral microbleeds are a potential neuroimaging biomarker of cerebral small vessel diseases that are prone to intracranial bleeding. We aimed to determine whether presence of cerebral microbleeds can identify patients at high risk of symptomatic intracranial haemorrhage when anticoagulated for atrial fibrillation after recent ischaemic stroke or transient ischaemic attack. Methods: Our observational, multicentre, prospective inception cohort study recruited adults aged 18 years or older from 79 hospitals in the UK and one in the Netherlands with atrial fibrillation and recent acute ischaemic stroke or transient ischaemic attack, treated with a vitamin K antagonist or direct oral anticoagulant, and followed up for 24 months using general practitioner and patient postal questionnaires, telephone interviews, hospital visits, and National Health Service digital data on hospital admissions or death. We excluded patients if they could not undergo MRI, had a definite contraindication to anticoagulation, or had previously received therapeutic anticoagulation. The primary outcome was symptomatic intracranial haemorrhage occurring at any time before the final follow-up at 24 months. The log-rank test was used to compare rates of intracranial haemorrhage between those with and without cerebral microbleeds. We developed two prediction models using Cox regression: first, including all predictors associated with intracranial haemorrhage at the 20% level in univariable analysis; and second, including cerebral microbleed presence and HAS-BLED score. We then compared these with the HAS-BLED score alone. This study is registered with ClinicalTrials.gov, number NCT02513316. Findings: Between Aug 4, 2011, and July 31, 2015, we recruited 1490 participants of whom follow-up data were available for 1447 (97%), over a mean period of 850 days (SD 373; 3366 patient-years). The symptomatic intracranial haemorrhage rate in patients with cerebral microbleeds was 9·8 per 1000 patient-years (95% CI 4·0–20·3) compared with 2·6 per 1000 patient-years (95% CI 1·1–5·4) in those without cerebral microbleeds (adjusted hazard ratio 3·67, 95% CI 1·27–10·60). Compared with the HAS-BLED score alone (C-index 0·41, 95% CI 0·29–0·53), models including cerebral microbleeds and HAS-BLED (0·66, 0·53–0·80) and cerebral microbleeds, diabetes, anticoagulant type, and HAS-BLED (0·74, 0·60–0·88) predicted symptomatic intracranial haemorrhage significantly better (difference in C-index 0·25, 95% CI 0·07–0·43, p=0·0065; and 0·33, 0·14–0·51, p=0·00059, respectively). Interpretation: In patients with atrial fibrillation anticoagulated after recent ischaemic stroke or transient ischaemic attack, cerebral microbleed presence is independently associated with symptomatic intracranial haemorrhage risk and could be used to inform anticoagulation decisions. Large-scale collaborative observational cohort analyses are needed to refine and validate intracranial haemorrhage risk scores incorporating cerebral microbleeds to identify patients at risk of net harm from oral anticoagulation. Funding: The Stroke Association and the British Heart Foundation

    Applications of graphene nanomaterials in energy storage—A state-of-art short review

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    The study presents the usage behavior of graphene in the energy field. Graphene has been comprehensively studied in the energy-related application due to higher conductivity and mechanical flexibility. The architecture of graphene permits it to strengthen and facilitate its application in the energy arena. Herein, the application of graphene in various energy storages such as fuel cells, dye-sensitized solar cells, batteries, nuclear power plants, and thermoelectric has been studied neatly. Graphene reacts towards these substances chemically, mechanically, and electrically to a great extend and appears with the excellent output of these objects. In the future graphene could be applied to the others field of energy and science successfully

    Queer In AI: A Case Study in Community-Led Participatory AI

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    Queerness and queer people face an uncertain future in the face of ever more widely deployed and invasive artificial intelligence (AI). These technologies have caused numerous harms to queer people, including privacy violations, censoring and downranking queer content, exposing queer people and spaces to harassment by making them hypervisible, deadnaming and outing queer people. More broadly, they have violated core tenets of queerness by classifying and controlling queer identities. In response to this, the queer community in AI has organized Queer in AI, a global, decentralized, volunteer-run grassroots organization that employs intersectional and community-led participatory design to build an inclusive and equitable AI future. In this paper, we present Queer in AI as a case study for community-led participatory design in AI. We examine how participatory design and intersectional tenets started and shaped this community’s programs over the years. We discuss different challenges that emerged in the process, look at ways this organization has fallen short of operationalizing participatory and intersectional principles, and then assess the organization’s impact. Queer in AI provides important lessons and insights for practitioners and theorists of participatory methods broadly through its rejection of hierarchy in favor of decentralization, success at building aid and programs by and for the queer community, and effort to change actors and institutions outside of the queer community. Finally, we theorize how communities like Queer in AI contribute to the participatory design in AI more broadly by fostering cultures of participation in AI, welcoming and empowering marginalized participants, critiquing poor or exploitative participatory practices, and bringing participation to institutions outside of individual research projects. Queer in AI’s work serves as a case study of grassroots activism and participatory methods within AI, demonstrating the potential of community-led participatory methods and intersectional praxis, while also providing challenges, case studies, and nuanced insights to researchers developing and using participatory methods

    Enhancing engine oil performance with graphene-cellulose nanoparticles: insights into thermophysical properties and tribological behavior

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    This study explores the development and optimization of a novel nano lubricant by incorporating graphene-cellulose nanoparticles into SAE 10W-40 engine oil to enhance its thermophysical and tribological performance. The nano lubricants were prepared with varying concentrations (0.01%, 0.03%, and 0.05% by volume) and subjected to a comprehensive evaluation of their thermal conductivity, dynamic viscosity, and tribological properties under operational conditions. The thermal conductivity analysis demonstrated that the inclusion of graphene-cellulose nanoparticles improved heat transfer capabilities, particularly at higher concentrations, while maintaining stability over a wide temperature range (30°C–90°C). The dynamic viscosity measurements revealed a synergistic effect of graphene and cellulose, enhancing dispersion stability and lubrication characteristics, with optimal performance achieved at 0.03% concentration. Tribological testing confirmed a significant reduction in the coefficient of friction, achieving a value as low as 0.0406, demonstrating improved wear resistance. Response Surface Methodology was employed to optimize the input parameters, providing insights into the interactions between concentration, load, speed, and temperature. The findings highlight the potential of graphene-cellulose nanocomposites as sustainable, high-performance additives for automotive lubricants, paving the way for energy-efficient and durable applications in the automotive and industrial sectors

    Effect of Enhancers and Inhibitors on Photocatalytic Sunlight Treatment of Methylene Blue

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    In view of the fatal illnesses caused by methylene blue (MB) which is contained in the dye wastewater, the present study focused on the use of natural sunlight in heterogeneous photocatalysis to decolorize and degrade MB. The present study also investigated the effects of enhancers (hydrogen peroxide and persulfate ion) and inhibitors (chloride and carbonate ions) on photodecolorization of MB. Pseudo-first-order rate constants for each studied effect were determined through Langmuir-Hinshelwood model. The recommended conditions to photodecolorize 60 ppm of MB under natural sunlight were 1.0 g/L of titanium dioxide nanopowder at initial pH 10.5 in order to achieve 85.3 % decolorization (rate constant of 10.8 × 10−3 min−1). The addition of 4,080 ppm of hydrogen peroxide and persulfate ion significantly enhanced the decolorization efficiency up to 96.6 and 99.3 %, respectively (rate constants of 66.2 and 91.0 × 10−3 min−1, respectively). However, the addition of 2,000 ppm of chloride and carbonate ions reduced the decolorization efficiency of MB to 74.7 and 70.2 %, respectively (rate constants of 7.8 and 7.3 × 10−3 min−1, respectively). The present study implied that it was possible to use natural sunlight as a light source for photocatalytic treatment of dye in tropical countries like Malaysia

    Queer In AI: A Case Study in Community-Led Participatory AI

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    We present Queer in AI as a case study for community-led participatory design in AI. We examine how participatory design and intersectional tenets started and shaped this community's programs over the years. We discuss different challenges that emerged in the process, look at ways this organization has fallen short of operationalizing participatory and intersectional principles, and then assess the organization's impact. Queer in AI provides important lessons and insights for practitioners and theorists of participatory methods broadly through its rejection of hierarchy in favor of decentralization, success at building aid and programs by and for the queer community, and effort to change actors and institutions outside of the queer community. Finally, we theorize how communities like Queer in AI contribute to the participatory design in AI more broadly by fostering cultures of participation in AI, welcoming and empowering marginalized participants, critiquing poor or exploitative participatory practices, and bringing participation to institutions outside of individual research projects. Queer in AI's work serves as a case study of grassroots activism and participatory methods within AI, demonstrating the potential of community-led participatory methods and intersectional praxis, while also providing challenges, case studies, and nuanced insights to researchers developing and using participatory methods.Comment: To appear at FAccT 202
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