Novel solutions to low-frequency problems with geometrically designed beam-waveguide systems

The poor low-frequency performance of geometrically designed beam-waveguide (BWG) antennas is shown to be caused by the diffraction phase centers being far from the geometrical optics mirror focus, resulting in substantial spillover and defocusing loss. Two novel solutions are proposed: (1) reposition the mirrors to focus low frequencies and redesign the high frequencies to utilize the new mirror positions, and (2) redesign the input feed system to provide an optimum solution for the low frequency. A novel use of the conjugate phase-matching technique is utilized to design the optimum low-frequency feed system, and the new feed system has been implemented in the JPL research and development BWG as part of a dual S-/X-band (2.3 GHz/8.45 GHz) feed system. The new S-band feed system is shown to perform significantly better than the original geometrically designed system

The Stochastic Container Relocation Problem

The Container Relocation Problem (CRP) is concerned with finding a sequence of moves of containers that minimizes the number of relocations needed to retrieve all containers, while respecting a given order of retrieval. However, the assumption of knowing the full retrieval order of containers is particularly unrealistic in real operations. This paper studies the stochastic CRP (SCRP), which relaxes this assumption. A new multi-stage stochastic model, called the batch model, is introduced, motivated, and compared with an existing model (the online model). The two main contributions are an optimal algorithm called Pruning-Best-First-Search (PBFS) and a randomized approximate algorithm called PBFS-Approximate with a bounded average error. Both algorithms, applicable in the batch and online models, are based on a new family of lower bounds for which we show some theoretical properties. Moreover, we introduce two new heuristics outperforming the best existing heuristics. Algorithms, bounds and heuristics are tested in an extensive computational section. Finally, based on strong computational evidence, we conjecture the optimality of the “Leveling” heuristic in a special “no information” case, where at any retrieval stage, any of the remaining containers is equally likely to be retrieved next

Flux pinning mechanism in BaFe1.9Ni0.1As2 single crystals: Evidence for fluctuation in mean free path induced pinning

The flux pinning mechanism of BaFe1.9Ni0.1As2 superconducting crystals have been investigated systematically by magnetic measurements up to 13 T at various temperatures. The field dependence of the critical current density, Jc, was analysed within the collective pinning model. A remarkably good agreement between the experimental results and theoretical dl pinning curve is obtained, which indicates that pinning in BaFe1.9Ni0.1As2 crystal originates from spatial variation of the mean free path. Moreover, the normalized pinning force density, Fp, curves versus h1/4B/Birr (Birr is the irreversibility field) were scaled using the Dew-Hughes model. Analysis suggests that point pinning alone cannot explain the observed field variation of Fp

DISPATCH: An Optimally-Competitive Algorithm for Maximum Online Perfect Bipartite Matching with i.i.d. Arrivals

This work presents an optimally-competitive algorithm for the problem of maximum weighted online perfect bipartite matching with i.i.d. arrivals. In this problem, we are given a known set of workers, a distribution over job types, and non-negative utility weights for each pair of worker and job types. At each time step, a job is drawn i.i.d. from the distribution over job types. Upon arrival, the job must be irrevocably assigned to a worker and cannot be dropped. The goal is to maximize the expected sum of utilities after all jobs are assigned. We introduce DISPATCH, a 0.5-competitive, randomized algorithm. We also prove that 0.5-competitive is the best possible. DISPATCH first selects a "preferred worker" and assigns the job to this worker if it is available. The preferred worker is determined based on an optimal solution to a fractional transportation problem. If the preferred worker is not available, DISPATCH randomly selects a worker from the available workers. We show that DISPATCH maintains a uniform distribution over the workers even when the distribution over the job types is non-uniform

Attitudes towards trusting artificial intelligence insights and factors to prevent the passive adherence of GPs: a pilot study

Artificial Intelligence (AI) systems could improve system efficiency by supporting clinicians in making appropriate referrals. However, they are imperfect by nature and misdiagnoses, if not correctly identified, can have consequences for patient care. In this paper, findings from an online survey are presented to understand the aptitude of GPs (n = 50) in appropriately trusting or not trusting the output of a fictitious AI-based decision support tool when assessing skin lesions, and to identify which individual characteristics could make GPs less prone to adhere to erroneous diagnostics results. The findings suggest that, when the AI was correct, the GPs’ ability to correctly diagnose a skin lesion significantly improved after receiving correct AI information, from 73.6% to 86.8% (X2 (1, N = 50) = 21.787, p < 0.001), with significant effects for both the benign (X2 (1, N = 50) = 21, p < 0.001) and malignant cases (X2 (1, N = 50) = 4.654, p = 0.031). However, when the AI provided erroneous information, only 10% of the GPs were able to correctly disagree with the indication of the AI in terms of diagnosis (d-AIW M: 0.12, SD: 0.37), and only 14% of participants were able to correctly decide the management plan despite the AI insights (d-AIW M:0.12, SD: 0.32). The analysis of the difference between groups in terms of individual characteristics suggested that GPs with domain knowledge in dermatology were better at rejecting the wrong insights from AI. View Full-Tex

Oropharyngeal candidiasis in hospitalised COVID-19 patients from Iran: Species identification and antifungal susceptibility pattern

Background: Emergence of coronavirus disease 2019 (COVID-19) is a major healthcare threat. Apparently, the novel coronavirus (SARS-CoV-2) is armed by special abilities to spread and dysregulate the immune mechanisms. The likelihood of oropharyngeal candidiasis (OPC) development in COVID-19 patients with a list of attributable risk factors for oral infections has not yet been investigated. Objectives: We here aim to investigate the prevalence, causative agents and antifungal susceptibility pattern of OPC in Iranian COVID-19 patients. Patients and Methods: A total of 53 hospitalised COVID-19 patients with OPC were studied. Relevant clinical data were mined. Strain identification was performed by 21-plex PCR and sequencing of the internal transcribed spacer region (ITS1-5.8S-ITS2). Antifungal susceptibility testing to fluconazole, itraconazole, voriconazole, amphotericin B, caspofungin, micafungin and anidulafungin was performed according to the CLSI broth dilution method. Results: In 53 COVID-19 patients with OPC, cardiovascular diseases (52.83) and diabetes (37.7) were the principal underlying conditions. The most common risk factor was lymphopaenia (71). In total, 65 Candida isolates causing OPC were recovered. C albicans (70.7) was the most common, followed by C glabrata (10.7), C dubliniensis (9.2), C parapsilosis sensu stricto (4.6), C tropicalis (3) and Pichia kudriavzevii (=C krusei, 1.5). Majority of the Candida isolates were susceptible to all three classes of antifungal drugs. Conclusion: Our data clarified some concerns regarding the occurrence of OPC in Iranian COVID-19 patients. Further studies should be conducted to design an appropriate prophylaxis programme and improve management of OPC in critically ill COVID-19 patients. © 2020 Blackwell Verlag Gmb

Safety and effectiveness of high-dose vitamin C in patients with COVID-19: a randomized open-label clinical trial

Background: Vitamin C is an essential water-soluble nutrient that functions as a key antioxidant and has been proven to be effective for boosting immunity. In this study, we aimed to assess the efficacy of adding high-dose intravenous vitamin C (HDIVC) to the regimens for patients with severe COVID-19 disease. Methods: An open-label, randomized, and controlled trial was conducted on patients with severe COVID-19 infection. The case and control treatment groups each consisted of 30 patients. The control group received lopinavir/ritonavir and hydroxychloroquine and the case group received HDIVC (6 g daily) added to the same regimen. Results: There were no statistically significant differences between two groups with respect to age and gender, laboratory results, and underlying diseases. The mean body temperature was significantly lower in the case group on the 3rd day of hospitalization (p = 0.001). Peripheral capillary oxygen saturations (SpO2) measured at the 3rd day of hospitalization was also higher in the case group receiving HDIVC (p = 0.014). The median length of hospitalization in the case group was significantly longer than the control group (8.5 days vs. 6.5 days) (p = 0.028). There was no significant difference in SpO2 levels at discharge time, the length of intensive care unit (ICU) stay, and mortality between the two groups. Conclusions: We did not find significantly better outcomes in the group who were treated with HDIVC in addition to the main treatment regimen at discharge. Trial registration irct.ir (IRCT20200411047025N1), April 14, 2020 © 2021, The Author(s)

Methyl-donor depletion of head and neck cancer cells in vitro establishes a less aggressive tumour cell phenotype

PURPOSE: DNA methylation plays a fundamental role in the epigenetic control of carcinogenesis and is, in part, influenced by the availability of methyl donors obtained from the diet. In this study, we developed an in-vitro model to investigate whether methyl donor depletion affects the phenotype and gene expression in head and neck squamous cell carcinoma (HNSCC) cells. METHODS: HNSCC cell lines (UD-SCC2 and UPCI-SCC72) were cultured in medium deficient in methionine, folate, and choline or methyl donor complete medium. Cell doubling-time, proliferation, migration, and apoptosis were analysed. The effects of methyl donor depletion on enzymes controlling DNA methylation and the pro-apoptotic factors death-associated protein kinase-1 (DAPK1) and p53 upregulated modulator of apoptosis (PUMA) were examined by quantitative-PCR or immunoblotting. RESULTS: HNSCC cells cultured in methyl donor deplete conditions showed significantly increased cell doubling times, reduced cell proliferation, impaired cell migration, and a dose-dependent increase in apoptosis when compared to cells cultured in complete medium. Methyl donor depletion significantly increased the gene expression of DNMT3a and TET-1, an effect that was reversed upon methyl donor repletion in UD-SCC2 cells. In addition, expression of DAPK1 and PUMA was increased in UD-SCC2 cells cultured in methyl donor deplete compared to complete medium, possibly explaining the observed increase in apoptosis in these cells. CONCLUSION: Taken together, these data show that depleting HNSCC cells of methyl donors reduces the growth and mobility of HNSCC cells, while increasing rates of apoptosis, suggesting that a methyl donor depleted diet may significantly affect the growth of established HNSCC