Fault Management in DC Microgrids:A Review of Challenges, Countermeasures, and Future Research Trends

The significant benefits of DC microgrids have instigated extensive efforts to be an alternative network as compared to conventional AC power networks. Although their deployment is ever-growing, multiple challenges still occurred for the protection of DC microgrids to efficiently design, control, and operate the system for the islanded mode and grid-tied mode. Therefore, there are extensive research activities underway to tackle these issues. The challenge arises from the sudden exponential increase in DC fault current, which must be extinguished in the absence of the naturally occurring zero crossings, potentially leading to sustained arcs. This paper presents cut-age and state-of-the-art issues concerning the fault management of DC microgrids. It provides an account of research in areas related to fault management of DC microgrids, including fault detection, location, identification, isolation, and reconfiguration. In each area, a comprehensive review has been carried out to identify the fault management of DC microgrids. Finally, future trends and challenges regarding fault management in DC-microgrids are also discussed

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

Offshore Wind Farm-Grid Integration: A Review on Infrastructure, Challenges, and Grid Solutions

Recently, the penetration of renewable energy sources (RESs) into electrical power systems is witnessing a large attention due to their inexhaustibility, environmental benefits, storage capabilities, lower maintenance and stronger economy, etc. Among these RESs, offshore wind power plants (OWPP) are ones of the most widespread power plants that have emerged with regard to being competitive with other energy technologies. However, the application of power electronic converters (PECs), offshore transmission lines and large substation transformers result in considerable power quality (PQ) issues in grid connected OWPP. Moreover, due to the installation of filters for each OWPP, some other challenges such as voltage and frequency stability arise. In this regard, various customs power devices along with integration control methodologies have been implemented to deal with stated issues. Furthermore, for a smooth and reliable operation of the system, each country established various grid codes. Although various mitigation schemes and related standards for OWPP are documented separately, a comprehensive review covering these aspects has not yet addressed in the literature. The objective of this study is to compare and relate prior as well as latest developments on PQ and stability challenges and their solutions. Low voltage ride through (LVRT) schemes and associated grid codes prevalent for the interconnection of OWPP based power grid have been deliberated. In addition, various PQ issues and mitigation options such as FACTS based filters, DFIG based adaptive and conventional control algorithms, ESS based methods and LVRT requirements have been summarized and compared. Finally, recommendations and future trends for PQ improvement are highlighted at the end

On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation

Constructing a robust model that can effectively generalize to test samples under distribution shifts remains a significant challenge in the field of medical imaging. The foundational models for vision and language, pre-trained on extensive sets of natural image and text data, have emerged as a promising approach. It showcases impressive learning abilities across different tasks with the need for only a limited amount of annotated samples. While numerous techniques have focused on developing better fine-tuning strategies to adapt these models for specific domains, we instead examine their robustness to domain shifts in the medical image segmentation task. To this end, we compare the generalization performance to unseen domains of various pre-trained models after being fine-tuned on the same in-distribution dataset and show that foundation-based models enjoy better robustness than other architectures. From here, we further developed a new Bayesian uncertainty estimation for frozen models and used them as an indicator to characterize the model's performance on out-of-distribution (OOD) data, proving particularly beneficial for real-world applications. Our experiments not only reveal the limitations of current indicators like accuracy on the line or agreement on the line commonly used in natural image applications but also emphasize the promise of the introduced Bayesian uncertainty. Specifically, lower uncertainty predictions usually tend to higher out-of-distribution (OOD) performance.Comment: Advances in Neural Information Processing Systems (NeurIPS) 2023, Workshop on robustness of zero/few-shot learning in foundation model

Effectiveness of perindopril/amlodipine fixed-dose combination in the treatment of hypertension: a systematic review

Background: Uncontrolled blood pressure is a major risk factor for cardiovascular diseases. Fixed-dose combination (FDC) therapy offers a promising approach to addressing this challenge by providing a convenient single-tablet solution that enhances the effectiveness of blood pressure control. In our systematic review, we assess the effectiveness of perindopril/amlodipine FDC in managing blood pressure.Methods: We conducted a comprehensive search across four primary electronic databases, namely, PubMed, Virtual Health Library (VHL), Global Health Library (GHL), and Google Scholar, as of 8 February 2022. Additionally, we performed a manual search to find relevant articles. The quality of the selected articles was evaluated using the Study Quality Assessment Tools (SQAT) checklist from the National Institute of Health and the ROB2 tool from Cochrane.Results: Our systematic review included 17 eligible articles. The findings show that the use of perindopril/amlodipine FDC significantly lowers blood pressure and enhances the quality of blood pressure control. Compared to the comparison group, the perindopril/amlodipine combination tablet resulted in a higher rate of blood pressure response and normalization. Importantly, perindopril/amlodipine FDC contributes to improved patient adherence with minimal side effects. However, studies conducted to date have not provided assessments of the cost-effectiveness of perindopril/amlodipine FDC.Conclusion: In summary, our analysis confirms the effectiveness of perindopril/amlodipine FDC in lowering blood pressure, with combination therapy outperforming monotherapy and placebo. Although mild adverse reactions were observed in a small subset of participants, cost-effectiveness assessments for this treatment remain lacking in the literature

An open label randomized controlled trial of tamoxifen combined with amphotericin B and fluconazole for cryptococcal meningitis

Background: Cryptococcal meningitis has high mortality. Flucytosine is a key treatment but is expensive and rarely available. The anti-cancer agent tamoxifen has synergistic anti-cryptococcal activity with amphotericin in vitro. It is off-patent, cheap, and widely available. We performed a trial to determine its therapeutic potential. Methods:Open label randomized controlled trial. Participants received standard care - amphotericin combined with fluconazole for the first two weeks - or standard care plus tamoxifen 300mg/day. The primary end point was Early Fungicidal Activity (EFA) - the rate of yeast clearance from cerebrospinal fluid (CSF). Trial registration https://clinicaltrials.gov/ct2/show/NCT03112031 . Results: 50 patients were enrolled, (median age 34 years, 35 male). Tamoxifen had no effect on EFA (- 0.48log10 colony-forming units/mL/CSF control arm versus -0.49 tamoxifen arm, difference - 0.005log10CFU/ml/day, 95%CI: -0.16, 0.15, P=0.95). Tamoxifen caused QTc prolongation. Conclusion: High dose tamoxifen does not increase the clearance rate of Cryptococcus from CSF. Novel, affordable therapies are needed. Funding:The trial was funded through the Wellcome Trust Asia Programme Vietnam Core Grant 106680 and a Wellcome Trust Intermediate Fellowship to JND grant number WT097147MA

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Effective traffic routing for urban transportation capacity and safety enhancement

Traffic routing is an essential service in most intelligent transportation systems (ITS), especially in urban traffic networks of large cities. However, this is a challenge issue as these traffic networks are complicated and traffic conditions change dynamically. Existing routing solutions from technology giants such as Google Maps, Waze are still insufficient in terms of accuracy (effectiveness) and efficiency (performance), especially applying in developing countries where traffic infrastructures have not yet matured enough, leading to degradation of transportation performance, safety while increasing traffic jam, economic loss, air and noise pollution. This work proposes an effective routing approach in large cities to avoid traffic congestion, enhancing transportation capacity and safety. Concretely, this work designed an appropriate urban traffic data organization scheme and devised a novel approach to searching solutions in an optimal routing algorithm, thus improve the routing performance significantly. Results from real-field experiments confirm the effectiveness and the efficiency of the proposed approaches which are prominent compared to the state-of-the-art solutions. The proposed approaches have been applied in a real urban traffic network of Ho Chi Minh City, the biggest city in Vietnam whose traffic is complicated. The experimental results and the practical deployed system reveal that the proposed mechanisms are ready to be applied in real-world applications