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We report a case of a 9-year-old girl presenting with unilateral retinal arteriovenous malformation (AVM) with symptomatic macular edema. Over 5 years of follow-up includes optical coherence tomography (OCT), fundus photographs, and fluorescein angiography at baseline and at follow-up. Systemic and neurologic workup was completed and negative for intracranial AVM. Vision has correlated with macular edema, ranging from 20/20 to 20/80. The patient has received nine injections of intravitreal bevacizumab and has not required an injection for the last couple of years. Follow-up is ongoing. [ABSTRACT FROM AUTHOR]

The omicron BA.1 bivalent booster is used globally. Previous open-label studies of the omicron BA.1 (Moderna mRNA-1273.214) booster showed superior neutralising antibody responses against omicron BA.1 and other variants compared with the original mRNA-1273 booster. We aimed to compare the safety and immunogenicity of omicron BA.1 monovalent and bivalent boosters with the original mRNA-1273 vaccine in a large, randomised controlled trial. In this large, randomised, observer-blind, active-controlled, phase 3 trial in the UK (28 hospital and vaccination clinic sites), individuals aged 16 years or older who had previously received two injections of any authorised or approved COVID-19 vaccine, with or without an mRNA vaccine booster (third dose), were randomly allocated (1:1) using interactive response technology to receive 50 μg omicron BA.1 monovalent or bivalent vaccines or 50 μg mRNA-1273 administered as boosters via deltoid intramuscular injection. The primary outcomes were safety and immunogenicity at day 29, including prespecified non-inferiority and superiority of booster immune responses, based on the neutralising antibody geometric mean concentration (GMC) ratios of the monovalent and bivalent boosters compared with mRNA-1273. Safety was assessed in all participants who received first or second boosters, and primary immunogenicity outcomes were assessed in all participants who received the planned booster dose, had pre-booster and day 29 antibody data, had no major protocol deviations, and who were SARS-CoV-2-negative. The study is registered with EudraCT (2022-000063-51) and ClinicalTrials.gov (NCT05249829) and is ongoing. Between Feb 16 and March 24, 2022, 724 participants were randomly allocated to receive omicron BA.1 monovalent (n=366) or mRNA-1273 (n=357), and between April 2 and June 17, 2022, 2824 participants were randomly allocated to receive omicron BA.1 bivalent (n=1418) or mRNA-1273 (n=1395) vaccines as second boosters. Median durations (months) between the most recent COVID-19 vaccine and study boosters were similar for omicron BA.1 monovalent (4·0 months [IQR 3·6–4·7]) and mRNA-1273 (4·1 [3·5–4·7]), and for the omicron BA.1 bivalent (5·5 [4·8–6·2]) and mRNA-1273 (5·4 [4·8–6·2]) boosters. The omicron BA.1 monovalent and bivalent boosters elicited superior neutralising GMCs against the omicron BA.1 variant compared with mRNA-1273, with GMC ratios of 1·68 (99% CI 1·45−1·95) and 1·53 (1·41−1·67) at day 29 post-booster doses in participants without previous SARS-CoV-2 infection. Both boosters induced non-inferior ancestral SARS-CoV-2 (Asp614Gly) immune responses with GMCs that were similar for the bivalent (2987·2 [95% CI 2814·9–3169·9]) versus mRNA-1273 (2911·3 [2750·9–3081·0]) and lower for the monovalent (2699·7 [2431·3–2997·7] vs 3020·6 [2776·5–3286·2]) boosters, with respective GMC ratios of 1·05 (99% CI 0·96–1·15) and 0·82 (95% CI 0·74–0·91). Results were comparable regardless of previous SARS-CoV-2 infection status. Incidences of solicited adverse reactions with the omicron BA.1 monovalent (335 [91·3%] of 367 participants) and omicron BA.1 bivalent (1285 [90·4%] of 1421 participants) boosters were similar to those observed previously for mRNA-1273, with no new safety concerns identified and no occurrences of fatal adverse events. Omicron-containing booster vaccines generated superior immunogenicity against omicron BA.1 and comparable immunogenicity against the original strain with no new safety concerns. It remains important to continuously monitor the immune responses and real-world vaccine effectiveness as divergent SARS-CoV-2 variants emerge. Moderna. [ABSTRACT FROM AUTHOR]

Objective: To report the incidence of postoperative epiretinal membrane (ERM) formation after primary pars plana vitrectomy (PPV) for giant retinal tear associated retinal detachment (GRT-RD) repair as well as its clinical characteristics and visual outcomes at a level one trauma and tertiary referral academic center. Patients and Methods: Patients with primary RD repair for GRT-RD at West Virginia University from September 2010 to July 2021 were identified using the ICD-10 codes (H33.031, H33.032, H33.033 and H33.039). Imaging studies including optical coherence tomography (OCT) were manually reviewed pre- and post-operatively for ERM formation after PPV for GRT-RD repair in patients who underwent PPV or combined PPV and scleral buckle (SB). Univariate analysis was performed to analyze clinical factors for ERM formation. Results: The study included 17 eyes of 16 patients who underwent PPV for GRT-RD. Postoperative ERM was observed in 70.6% (13 of 17 eyes) of the patients. Anatomic success was achieved in all patients. The mean (range) preoperative and final best corrected visual acuity (BCVA) in logMAR units by macula status was 0.19 (0– 0.5) and 0.28 (0– 0.5) for macula-on and 1.7 (0.5– 2.3) and 0.7 (0.2– 1.9) for macular-off GRT-RDs. Clinical variables including use of medium-term tamponade with perfluorocarbon liquid (PFCL), cryopexy, endodiathermy, number of tears or total clock hours of tears did not correlate with an increased risk of ERM formation. Conclusion: Post-vitrectomized eyes for GRT-RD repair have a significantly higher incidence of ERM formation, nearing 70% in our study. Surgeons may consider prophylactic ILM peel at the time of removal of tamponade agents or weigh in ILM peel at the time of primary repair, a more challenging surgical technique in our opinion. [ABSTRACT FROM AUTHOR]

Cement-based sensors include conductive fillers to achieve a sensing capability based on the piezoresistivity phenomenon, in which the electrical resistivity changes with strain. The microstructural characterisation of cement-based sensors can be obtained using a promising non-destructive technique, such as AC impedance spectroscopy (ACIS), which has been recently used by many researchers. This paper reviews the fundamental concepts of piezoresistivity and ACIS in addition to the comparison of equivalent circuit models of cement-based sensors found in the literature. These concepts include piezoresistivity theory, factors affecting piezoresistivity measurement, resistance measurement methodology, strain/damage sensing, causes of piezoresistivity, theories of conduction, AC impedance spectroscopy theory, and the equivalent circuit model. This review aims to provide a comprehensive guide for researchers and practitioners interested in exploring and applying different techniques to self-sensing concrete. [ABSTRACT FROM AUTHOR]

The article discusses explores American agricultural exports to the Association of Southeast Asian Nations (ASEAN) and discuss why it is good candidate for expanding agricultural exports. Topics discussed include issues that can lead to devastating trading relationships trading partners where it discusses limited market diversification as one of the reasons, mentions that ASEAN has been one of the fastest growing economic blocs in the world and discussed America agricultural export to ASEAN.

A quasi-experimental field study was undertaken to examine whether the source credibility of point-of-decision (POD) prompts would affect their effectiveness in increasing stair use. POD prompts attributed either to a more credible source, a less credible source, or nothing were randomly installed in three student halls of residence at a public university in Hong Kong (plus a control). The stair and elevator use of residents were recorded by view-from-top surveillance cameras and counted using motion-detection software, resulting in 14,189 observations. The findings show that all the POD prompts can yield, as hypothesized, a significant positive effect on stair use. The relative increase in stair use was 2.49% on average. However, contrary to our second hypothesis, the POD prompt attributed to the more credible source was not the most effective intervention. The implications of these findings are discussed in conclusion. [ABSTRACT FROM AUTHOR]

• CO adsorption induces agglomeration of isolated Pd atoms. • The rate of H 2 permeation across PdCu decreases with increasing CO concentration. • CO inhibits H 2 transport by adsorbing only on Pd sites and blocking H 2 dissociation. • PdCu is more resistant to CO poisoning than Pd. Pd and PdCu alloy membranes are promising candidates for separating hydrogen from mixed gas streams due in part to their infinite selectivity to hydrogen separation. However, other gases such as CO can inhibit hydrogen transport across Pd-based membranes. In this work, the mechanism by which CO inhibits hydrogen transport across a 25 μm-thick Pd 47 Cu 53 (mol%) membrane is investigated by operando infrared-reflection absorption spectroscopy (IRAS) in the 373–533 K temperature range. In the absence of hydrogen, CO adsorbs on three different sites on the PdCu surface: (1) bridging between contiguous Pd atoms, (2) on top of isolated Pd atoms surrounded by Cu atoms, and (3) on top of oxidized Cu atoms. CO induces agglomeration of isolated Pd atoms on the PdCu surface, which is driven by the higher stability of CO adsorbed on bridging sites between Pd atoms than on isolated Pd atoms surrounded by Cu atoms. The rate of hydrogen permeation across the PdCu alloy membrane decreases with increasing CO concentration in the feed gas, and the poisoning effect of CO is more severe at lower temperatures. CO inhibits hydrogen transport across the membrane by adsorbing only on Pd sites on the PdCu surface and blocking H 2 dissociation on these sites. Due to the weaker interaction of CO with PdCu alloy surfaces than with Pd, the PdCu alloy is more resistant to CO poisoning than pure Pd. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate prognostic factors and survival of patients with sebaceous carcinoma of the eyelid through a population-based analysis. Methods: A total of 940 patients with primary sebaceous carcinoma of the eyelid were derived from the Surveillance, Epidemiology, and End Results (SEER) database in the United States from 1973 to 2013. Kaplan–Meier univariate analysis and Cox Regression multivariate analysis were performed to examine prognostic factors in overall survival (OS). 5- and 10-year survival rates, median survival, and prognostic variables with statistical significance were measured. Results: Kaplan-Meier analysis showed that OS is 66% and 44% at 5 years and 10 years respectively. Median OS is 9.4 years. Multivariate Cox regression analysis demonstrated that independent prognostic factors for OS are age at diagnosis (HR = 4.61 [95% CI 1.93–11.0], P = 0.001), surgical treatment (HR = 0.196 [95% CI 0.07–0.55], P = 0.002), combined surgical and radiation treatment (HR = 0.227 [95% CI 0.06–0.81], P = 0.023), and greater tumor size at diagnosis (HR = 3.381, [95% CI 1.77–6.45], P < 0.001). Conclusion: We report the largest population study to date to evaluate prognostic factors of patients with sebaceous carcinoma of the eyelid. Multivariate analysis shows that older age, and greater tumor size correlate with decreased overall survival, whereas surgical treatment or combined surgical and radiation treatment correlate with increased overall survival. Interestingly, tumor grade, lymph node involvement, and distant extent of tumor have not demonstrated to be independent prognostic factors for overall survival. [ABSTRACT FROM AUTHOR]

A 72-year-old male with history of monocular vision with complete vision loss in his right eye from previous retinal detachment presented with 20/200 vision in the left eye with a corneal ulcer. Culture was obtained, and the patient was started on fortified tobramycin, fortified vancomycin, and amphotericin. Despite the antibiotics, the patient did not significantly improve, after which another culture was obtained before the patient was taken to the surgery for cryotherapy and a partial conjunctival flap. The culture identified Chryseobacterium indologenes. There have been fewer than a handful of cases reported in the last three decades with different antibiotic susceptibility profiles. Our patient was successfully treated with ciprofloxacin and ceftazidime with the final vision of 20/40. [ABSTRACT FROM AUTHOR]

Between 1843 and 1873, British Hong Kong extradited hundreds of Chinese fugitives under treaty for crimes ranging from piracy to slave trading. The story of this regime has never been told, even though it produced the only extradition case to reach the Judicial Committee of the Privy Council during the nineteenth century. Although the case in question, Attorney General of Hong Kong v Kwok-A-Sing (1873), has received scholarly attention, it has been read mostly as proof of prevailing British contempt for Chinese sovereignty. An examination of legal practice over a longer period reveals a more ambivalent reality. Complex circumstances, including local resource constraints and the perceived difficulties of meting out English justice to Chinese subjects, encouraged British officials to strategically disclaim jurisdiction over them. Extradition was used instead to maintain colonial order in Hong Kong, and to further British interests in China, at minimal economic and political cost. [ABSTRACT FROM AUTHOR]

With the expected increase in warmer conditions caused by climate change, heat-related illnesses are becoming a more pressing issue. One way that humans can protect themselves from this is to seek shade. The design of urban spaces can provide individuals with a variety of ways to obtain this shade. The objective of this study was to perform a detailed evaluation and comparison of three shading strategies that could be used in an urban environment: shade from a building, from a tree, and from an umbrella. This was done through using field measurements to calculate the impact of each strategy on a thermal comfort index (Comfort Formula (COMFA)) in two urban settings during sunny days of the summer of 2013 and 2014 in London, Canada. Building shade was found to be the most effective cooling strategy, followed by the tree strategy and the umbrella strategy. As expected, the main determinant of this ranking was a strategy's ability to block incoming shortwave radiation. Further analysis indicated that changes in the convective loss of energy and in longwave radiation absorption had a smaller impact that caused variations in the strategy effectiveness between settings. This suggests that under non-sunny days, these rankings could change. [ABSTRACT FROM AUTHOR]

Transmembrane hydrogen flux of a novel 1 μm palladium membrane, supported by a nickel microstructured support grid, is characterized when exposed to carbon dioxide, carbon monoxide and water vapor over a range of temperature from 235° to 320 °C. At all temperatures, the palladium membrane is found to be primarily hydrogen transport rate limited due to surface reactions, not atomic hydrogen solution-diffusion though the bulk palladium membrane. Hydrogen flux decreases rapidly as contaminate gas concentration increases, before reaching a temperature dependent steady state, due to nearly complete surface coverage of the palladium by adsorbed contaminate. Carbon monoxide and carbon dioxide have the largest impact, while water vapor has a lesser impact. The likely source of deactivation is the blocking of surface active sites by adsorbed contaminate molecules. Independent of contaminate gas effects, this study reveals a permanent hydrogen flux decrease due to diffusion of nickel from the microstructured support grid into the palladium membrane at temperatures above 360 °C. [ABSTRACT FROM AUTHOR]

Food allergy is a significant medical problem that affects up to 8% of children in developed countries. At present, there are no curative therapies available in routine practice and management of food allergy involves strict allergen avoidance, education, and prompt treatment upon accidental exposure. Oral immunotherapy ( OIT) is an efficacious experimental approach to food allergy and has been shown to provide a substantial benefit in terms of allergen desensitization. However, OIT is associated with high rates of allergic reactions, and the period of protection offered by OIT appears to be limited and highly variable. Recurrence of allergen sensitivity after a period of treatment discontinuation is commonly observed. With the aim of overcoming these limitations of OIT, several trials have studied omalizumab (anti-IgE monoclonal antibody) as an adjuvant treatment for patients undergoing OIT. Results from these trials have shown that the addition of omalizumab to OIT leads to a significant decrease in the frequency and severity of reactions, which allows for an increase in the threshold of tolerance to food allergens. This review provides a summary of the current literature and addresses some of the key questions that remain regarding the use of omalizumab in conjunction with OIT. [ABSTRACT FROM AUTHOR]

Objective To evaluate prognostic factors of patients with chordoma through a population-based analysis. Methods Surveillance, Epidemiology, and End Results (SEER) database was queried for patients with chordoma from 1973 to 2013. Kaplan-Meier univariate analysis and Cox regression multivariate analysis were performed to examine prognostic factors in overall survival (OS) and disease-specific survival (DSS). Results One thousand five hundred ninety-eight patients with chordoma are identified. Kaplan-Meier analysis showed that OS and DSS were 61% and 71% at 5 years and 41% and 57% at 10 years. Multivariate Cox regression analysis demonstrated that independent predictors of OS and DSS are age at diagnosis (hazard ratio [HR]= 2.80 [95% confidence interval {CI}, 2.12–3.70], P < 0.001; HR = 1.60 [95% CI, 1.18–2.16], P = 0.002), surgical treatment (HR = 0.62 [95% CI, 0.52–0.73], P < 0.001; HR = 0.64 [95% CI, 0.52–0.79], P < 0.001), radiation therapy (HR = 1.23 [95% CI, 1.07–1.42], P = 0.004; HR = 1.29 [95% CI, 1.09–1.54], P = 0.004), tumor size (HR = 1.53 [95% CI, 1.32–1.78], P < 0.001; HR = 1.62 [95% CI, 1.35–1.94], P < 0.001) and distant metastasis (HR = 3.40 [95% CI, 2.45–4.71], P < 0.001; HR = 3.77 [95% CI, 2.61–5.45], P < 0.001). Conclusion We report the largest study to date to evaluate prognostic factors of patients with chordoma. Multivariate analysis demonstrated that older age, greater tumor size, and distant metastasis were correlated with decreased survival, whereas surgical resection was correlated with increased survival. Patients receiving radiation therapy also showed decreased survival, likely an indication of the patients' advanced stage of disease, making them poor surgical candidates. [ABSTRACT FROM AUTHOR]

The growth of oxygenated carbonaceous (oxy-carbon) species on the surface of Pt/Al 2 O 3 during total oxidation of propane is analyzed in detail—including their composition, their location on the catalyst surface, their reactivity, and their role in the propane oxidation mechanism—by in situ diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS). Platinum nanoparticles catalyze the transformation of propane into many different oxy-carbon surface species, including acetate, enolate, aliphatic ester, and acetone, which spillover and grow on the Al 2 O 3 support. There is no correlation between the concentration of oxy-carbon surface species and the rate of CO 2 production in the gas-phase, which indicates that these species are inert spectators in the propane oxidation mechanism. Temperature-programmed oxidation of the oxy-carbon surface species reveals that enolate, aliphatic ester, and acetone species are removed from the surface by combustion at similar temperatures with an activation barrier of 112 kJ/mol, whereas acetate species are removed at higher temperatures with an activation barrier of 147 kJ/mol. Both the formation and combustion of oxy-carbon surface species occur in pathways that are parallel to, and orders-of-magnitude slower than, the main pathway to CO 2 production. [ABSTRACT FROM AUTHOR]

When data mining techniques are applied to discover useful knowledge behind a large data collection, they are often required to preserve some confidential information, such as sensitive frequent itemsets, rules and so on. A feasible way to ensure the confidentiality is to sanitize the database and conceal sensitive information. However, the sanitization process often produces side effects, thus minimizing these side effects is an important task. An important but ignored fact is that a tradeoff exists within different side effects. When attempting to improve the performance on one dimension, the performance on other dimensions often will be degraded. In this paper, we focus on privacy preserving in association rule mining. Since there is a tradeoff within different side effects, we tried to minimize them from the view of multi-objective optimization. A rule hiding approach based on evolutionary multi-objective optimization (EMO) is proposed. It hides sensitive rules through removing identified items. The side effects on missing non-sensitive rules, ghost rules and data loss are formulated as optimization objectives. EMO is utilized to find a suitable subset of transactions for modification so that side effects can be minimized. Experimental results on real datasets illustrate that the proposed approach can achieve satisfactory results with fewer side effects. In addition, the EMO-based approach can produce multiple hiding solutions in a single run. It provides the opportunity for a user to choose freely the preferred one by preference or experience. [ABSTRACT FROM AUTHOR]

This paper provides a review of progress in catalytic conversion of JP-8 fuel and its surrogates made over the last decade. The effect of different types of catalyst and support materials, as well as different preparation methods, is discussed in detail. The derivation of kinetic models for computational studies is also examined. Particular attention is given to the development of sulfur tolerant catalysts and the mechanisms by which catalyst poisoning occurs, as this is an important obstacle to overcome for systems using sulfur-laden fuel. Suggestions for further research are offered. [ABSTRACT FROM AUTHOR]

Oxidation behavior of dodecane and two mixtures of dodecane and m-xylene (90/10 wt.% and 80/20 wt.%) over an Rh catalyst in a meso-scale heat recirculating combustor was examined to isolate the effect of aromatic content on performance. The fuel conversion, product selectivities, and reaction kinetics were calculated, and the global combustion behavior observed. The results showed that increasing the amount of m-xylene in the fuel increased the fuel conversion from 85% (pure dodecane) to 92% (90/10) and further to 98% (80/20). The presence of xylene also significantly increased CO 2 /H 2 O selectivity and decreased CO/H 2 selectivity. Global activation energy increased linearly with increase in xylene content, supporting that addition of aromatic species to fuel lowers the overall reactivity. The non-catalytic reaction was also simulated using Chemkin software to determine the effect of the Rh catalyst on the combustor performance and to analyze the difference in chemical mechanisms. The results revealed that the catalyst promotes total oxidation over partial oxidation, and lowers the global activation energy by up to 70%. [ABSTRACT FROM AUTHOR]

Summary Circadian behavior in mammals is orchestrated by neurons within the suprachiasmatic nucleus (SCN), yet the neuronal population necessary for the generation of timekeeping remains unknown. We show that a subset of SCN neurons expressing the neuropeptide neuromedin S (NMS) plays an essential role in the generation of daily rhythms in behavior. We demonstrate that lengthening period within Nms neurons is sufficient to lengthen period of the SCN and behavioral circadian rhythms. Conversely, mice without a functional molecular clock within Nms neurons lack synchronous molecular oscillations and coherent behavioral daily rhythms. Interestingly, we found that mice lacking Nms and its closely related paralog, Nmu , do not lose in vivo circadian rhythms. However, blocking vesicular transmission from Nms neurons with intact cell-autonomous clocks disrupts the timing mechanisms of the SCN, revealing that Nms neurons define a subpopulation of pacemakers that control SCN network synchrony and in vivo circadian rhythms through intercellular synaptic transmission. [ABSTRACT FROM AUTHOR]

The results obtained from the combustion behavior of propane over platinum and rhodium catalysts in a meso-scale heat recirculating combustor are presented. The extinction limits, conversion, product selectivity/yield, and activation energy using the two catalysts were compared in an effort to predict their performance using a liquid fuel. The extinction limits were also compared to those of non-catalytic combustion in the same combustor. The results showed that the use of a catalyst greatly expanded the range of stable operating conditions, in terms of both extinction limits and flow rates supported. The Rh catalyst was found to exhibit a higher propane conversion rate, reaching a maximum of 90.4% at stoichiometric conditions (as compared to only 61.4% offered by the Pt catalyst under lean conditions), but the Pt catalyst had superior CO 2 selectivity for most of the examined conditions, indicating more of the heat released being used for product formation as opposed to being lost to the environment. However, despite having a higher rate of heat loss, the combustion with the Rh catalyst produced an overall higher amount of enthalpy than the Pt due to its superior fuel conversion. The Pt catalyst also had a significantly smaller activation energy (13.8 kJ/mol) than the Rh catalyst (74.7 kJ/mol), except at equivalence ratios richer than Φ = 1.75 (corresponding to catalyst temperatures below 500 °C), where it abruptly changed to 211.4 kJ/mol, signifying a transition from diffusion-limited reactions to kinetically limited reactions at this point. The results reveal that Rh would be a more suitable catalyst for use in liquid-fueled meso-scale combustors, as fuel conversion has been found to be a limiting factor for combustion stability in these systems, and as its higher output energy allows for greater flexibility of use. [ABSTRACT FROM AUTHOR]

A frequency‐based image deblurring method is proposed. Unlike the traditional ways of replicating target images, a periodic point spread function (PSF) is constructed. By investigating the periodic PSF under the Fourier domain, it has been found that noises at different frequencies produce significantly varying impacts on the reconstruction quality. Therefore, the Fourier slice theorem is utilised to select partial Fourier samples and to avoid the noises that can severely damage performance. A sparse‐inducing method is then developed to recover a clear image from the selected Fourier samples. [ABSTRACT FROM AUTHOR]

Group activity recognition is a central theme in many domains, such as sports video analysis, CCTV surveillance, sports tactics, and social scenario understanding. However, there are still challenges in embedding actors' relations in a multi-person scenario due to occlusion, movement, and light. Current studies mainly focus on collective and individual local features from the spatial and temporal perspectives, which results in inefficiency, low robustness, and low portability. To this end, a Spatio-Temporal Attention-Based Graph Convolution Network (STAB-GCN) model is proposed to effectively embed deep complex relations between actors. Specifically, we leverage the attention mechanism to attentively explore spatio-temporal latent relations between actors. This approach captures spatio-temporal contextual information and improves individual and group embedding. Then, we feed actor relation graphs built from group activity videos into our proposed STAB-GCN for further inference, which selectively attends to the relevant features while ignoring those irrelevant to the relation extraction task. We perform experiments on three available group activity datasets, acquiring better performance than state-of-the-art methods. The results verify the validity of our proposed model and highlight the obstructive impacts of spatio-temporal attention-based graph embedding on group activity recognition. [ABSTRACT FROM AUTHOR]

Observational studies have identified the potential prognostic value for severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) viral load and anti‐SARS‐CoV‐2 antibodies in coronavirus disease 2019 (COVID‐19). However, viral load in nasopharyngeal (NP) swabs produced inconsistent results in prognostic analyses, and the prognostic value of viral load or antibodies has not been confirmed in large clinical trials. COVACTA and REMDACTA were double‐blind, randomized, controlled trials with a combined enrollment of 1078 patients hospitalized with COVID‐19 treated with tocilizumab or placebo in COVACTA or tocilizumab plus remdesivir or placebo plus remdesivir in REMDACTA. We assessed the potential prognostic value of NP and serum SARS‐CoV‐2 viral load and serum anti‐SARS‐CoV‐2 antibodies at baseline as biomarkers for clinical outcomes in patients enrolled in these trials. In adjusted Cox proportional hazard models, serum viral load was a more reliable predictor of clinical outcomes than NP viral load; high serum viral load was associated with higher risk for death and mechanical ventilation/death and lower likelihood of hospital discharge (high vs. negative viral load hazard ratios [95% confidence interval {CI}] were 2.87 [1.57–5.25], 3.86 [2.23–6.68], and 0.23 [0.14–0.36], respectively, in COVACTA and 8.11 [2.95–22.26], 10.29 [4.5–23.55], and 0.21 [0.15–0.29], respectively, in REMDACTA) and high serum viral load correlated with levels of inflammatory cytokines and lung damage biomarkers. High anti‐SARS‐CoV‐2 spike protein antibody (ACOV2S) levels were associated with higher likelihood of hospital discharge (high vs. below the limit of quantification hazard ratios [95% CI] were 2.55 [1.59–4.08] for COVACTA and 1.54 [1.13–2.09] for REMDACTA). These results support the role of baseline SARS‐CoV‐2 serum viral load and ACOV2S antibody titers in predicting clinical outcomes for patients hospitalized with COVID‐19. [ABSTRACT FROM AUTHOR]

Anomaly analytics is a popular and vital task in various research contexts that has been studied for several decades. At the same time, deep learning has shown its capacity in solving many graph-based tasks, like node classification, link prediction, and graph classification. Recently, many studies are extending graph learning models for solving anomaly analytics problems, resulting in beneficial advances in graph-based anomaly analytics techniques. In this survey, we provide a comprehensive overview of graph learning methods for anomaly analytics tasks. We classify them into four categories based on their model architectures, namely graph convolutional network, graph attention network, graph autoencoder, and other graph learning models. The differences between these methods are also compared in a systematic manner. Furthermore, we outline several graph-based anomaly analytics applications across various domains in the real world. Finally, we discuss five potential future research directions in this rapidly growing field. [ABSTRACT FROM AUTHOR]

In this work, we describe a spectroscopic membrane permeation cell that we have designed and fabricated to enable—for the first time—the surface of metal membranes to be analyzed by infrared-reflection absorption spectroscopy (IRAS) while simultaneously measuring the rate of hydrogen permeation across the membrane under realistic permeation conditions. As a proof-of-concept, we demonstrate that the permeation cell can (1) accurately measure the rate of H 2 permeation across a 25 µm-thick Pd foil membrane, (2) detect sub-monolayer coverages of CO on the membrane surface in the 333–533 K temperature range, and (3) measure the rate of H 2 permeation across the membrane while simultaneously detecting surface-adsorbed CO during exposure to H 2 /CO gas mixtures at 533 K. IRAS spectra recorded during exposure to H 2 /CO gas mixtures at 533 K indicate that CO dissociates on the membrane surface, and C–H bonds are formed, which modify the surface adsorption properties of the membrane and result in irreversible losses in the H 2 flux across the membrane. With this spectroscopic membrane permeation cell, it is possible to correlate microscopic surface processes to macroscopic rates of permeation across the membrane, which will enable the rational design of new membrane materials that are resistant to deactivation. [ABSTRACT FROM AUTHOR]

Evaluating the impact of a scholarly article is of great significance and has attracted great attentions. Although citation-based evaluation approaches have been widely used, these approaches face limitations e.g. in identifying anomalous citations patterns. This negligence would inevitably cause unfairness and inaccuracy to the article impact evaluation. In this study, in order to discover the anomalous citations and ensure the fairness and accuracy of research outcome evaluation, we investigate the citation relationships between articles using the following factors: collaboration times, the time span of collaboration, citing times and the time span of citing to weaken the relationship of Conflict of Interest (COI) in the citation network. Meanwhile, we study a special kind of COI, namely suspected COI relationship. Based on the COI relationship, we further bring forward the COIRank algorithm, an innovative scheme for accurately assessing the impact of an article. Our method distinguishes the citation strength, and utilizes PageRank and HITS algorithms to rank scholarly articles comprehensively. The experiments are conducted on the American Physical Society (APS) dataset. We find that about 80.88% articles contain contributed citations by co-authors in 26,366 articles and 75.55% articles among these articles are cited by the authors belonging to the same affiliation, indicating COI and suspected COI should not be ignored for evaluating impact of scientific papers objectively. Moreover, our experimental results demonstrate COIRank algorithm significantly outperforms the state-of-art solutions. The validity of our approach is verified by using the probability of Recommendation Intensity. [ABSTRACT FROM AUTHOR]

With the rapid development of information and communication technologies, people are increasingly referring to web information to assist in their travel planning and decision making. Research shows that people conduct collaborative information searches while planning their travel activities online. However, little is known in depth about tourists' online collaborative search. This study examines tourists' collaborative information search behavior in detail, including their search stages, online search strategies, and information flow breakdowns. The data for analysis included pre- and postsearch questionnaires, web search and chat logs, and postsearch interviews. A model of tourist collaborative information retrieval was developed. The model identified collaborative planning, collaborative information searching, sharing of information, and collaborative decision making as four stages of tourists' collaborative search. The results show that tourists collaborated by planning their search strategies, dividing search tasks into subtasks and allocating workload, using search queries and URL links recommended by teammates, and discussing search results together. Related personal knowledge and experiences appeared important in trip planning and collaborative information search. During the collaborative search, tourists also encountered various information flow breakdowns in different search stages. These were classified and their effects on collaborative information search were reported. Implications for system design in support of collaborative information retrieval in travel contexts are also discussed. [ABSTRACT FROM AUTHOR]

In this work, a boundary layer fluid dynamics model is used to numerically investigate the heterogeneous/homogeneous combustion of n -dodecane in a platinum coated channel. An elementary lumped surface chemistry model is used to describe the oxidation of n -dodecane and its intermediates on Pt. A parallel plate microcombustor with Pt-coated walls was designed based on findings from the model. Experimental analysis of the n -dodecane/air fueled parallel plate microcombustor with Pt-coated walls shows that the combustor is capable of complete oxidation while operating at high temperatures (>1100 K) relevant to next generation thermal-to-electric power conversion. Chemiluminescence imaging in the combustor suggests that a weak flame exists, which is capable of driving oxidation to completion while avoiding extreme temperatures. This reactor shows promise as a heat source for high temperature compact thermal-to-electric power conversion. [ABSTRACT FROM AUTHOR]

Some individuals show severe cognitive impairment when sleep deprived, whereas others are able to maintain a high level of performance. Such differences are stable and trait-like, but it is not clear whether these findings generalize to physiologic responses to sleep loss. Here, we analyzed individual differences in behavioral and physiologic measures in healthy ethnic-Chinese male volunteers ( n = 12; aged 22-30 years) who were kept awake for at least 26 h in a controlled laboratory environment on two separate occasions. Every 2 h, sustained attention performance was assessed using a 10-min psychomotor vigilance task ( PVT), and sleepiness was estimated objectively by determining percentage eyelid closure over the pupil over time ( PERCLOS) and blink rate. Between-subject differences in heart rate and its variability, and electroencephalogram ( EEG) spectral power were also analyzed during each PVT. To assess stability of individual differences, intraclass correlation coefficients ( ICC) were determined using variance components analysis. Consistent with previous work, individual differences in PVT performance were reproducible across study visits, as were baseline sleep measures prior to sleep deprivation. In addition, stable individual differences were observed during sleep deprivation for PERCLOS, blink rate, heart rate and its variability, and EEG spectral power in the alpha frequency band, even after adjusting for baseline differences in these measures (range, ICC = 0.67-0.91). These findings establish that changes in ocular, ECG, and EEG signals are highly reproducible across a night of sleep deprivation, hence raising the possibility that, similar to behavioral measures, physiologic responses to sleep loss are trait-like. [ABSTRACT FROM AUTHOR]

Since many buildings in Canada were built prior to the advent of national and provincial energy codes and standards, quantifying building envelope thermal performance is an important step in identifying retrofit opportunities in existing buildings. This study aimed to use external quantitative infrared thermography (IRT) to estimate effective U-value of opaque building envelopes (considering the effect of thermal bridging sources) of a conditioned at-scale structure comprised of four wood-framed wall assemblies commonly used in Canada. Furthermore, the effect of vignetting artefacts on effective U-value measurements was assessed, followed by a practical approach to correcting for it to improve accuracy of U-value estimation and calibration of energy models. Additionally, a comprehensive uncertainty analysis was performed to evaluate the impact of input variables on the accuracy and uncertainty of results. Finally, apart from qualitative and quantitative thermal assessment of the building envelope, a novel relative quantitative infrared index (IRI) methodology was proposed as a means to facilitate rapid evaluation and subsequent ranking of building envelope thermal performance. The results indicated that vignetting effect has an adverse impact on the accuracy of results, in particular for well-insulated walls where deviations of −42.31% to −83.33% were observed. However, when the proposed practical approach was implemented, substantial improvements in accuracy of walls' U-value were obtained, ranging from −2.33% to −12.50% after correction versus −13.95% to −58.33% without correction. Moreover, the results indicated that the energy model was substantially more accurate when the effect of thermal bridges were accounted for, and the adverse effect of vignetting was addressed in the estimation of U-value. In this case, ASHRAE Guideline 14 criteria were satisfied: Normalized Mean Bias Error (NMBE) < 5%, and Coefficient of Variation of the Root Mean Square Error (CVRMSE) < 15%. The findings of the uncertainty budget demonstrated that the influence of parameters on U-value depends on the type of wall assembly. Ultimately, wall thermal performance rankings based on IRI were consistent with their U-value rankings, implying that IRI can be a reliable metric for relative quantitative comparison of building envelope thermal performance, regardless of boundary conditions. [ABSTRACT FROM AUTHOR]

Many challenges persist with traditional self-sensing cementitious composites, such as selecting conductive fillers, determining optimal aspect ratios, controlling dosage, achieving filler dispersion, designing practical electrodes, and overcoming fabrication difficulties. Therefore, this paper proposes a novel self-sensing technique for cementitious composites by incorporating a 2-dimensional (2-D) carbon-fibre textile network to address these challenges. Additionally, instead of using the entire composite volume as the sensor, an alternative approach is explored, which involves utilising the interlaminar interface by incorporating the 2-D carbon-fibre textile network. This approach provides an integrated self-sensing system, including electrical leads and conductive pathways, which can be tailored based on the design requirements. The paper introduces fundamental concepts and measurement circuit design, followed by a comprehensive study covering measurement techniques, electromechanical properties, and microstructural analysis. Furthermore, it discusses the impact of ambient conditions, such as temperature and relative humidity, on the measurements. Experimental results demonstrate a remarkable maximum fractional change in contact resistivity, reaching up to 70%. The reversibility during cyclic compression is excellent, with a maximum negative gauge factor of − 2500. These findings represent a significant step toward achieving a practical and simplified method for manufacturing self-sensing cementitious composites and open avenues for self-sensing, sustainable textile-reinforced concrete structures (TRC). [Display omitted] • A novel self-sensing system for cementitious composites has been introduced. • The system can be considered as an integrated solution, encompassing the essential components required for self-sensing. • A simplified equivalent circuit model and an equation to calculate the overall contact resistivity have been proposed. • A remarkable maximum fractional change in the overall contact resistivity, reaching up to 70%, has been achieved. • The reversibility during cyclic compression has been excellent, with a maximum negative gauge factor of − 2500. [ABSTRACT FROM AUTHOR]

The sparse feature sphere centroid (SFSC) classifier for face recognition is proposed. SFSC is based on nearest feature plane (NFP), sparse representation classification (SRC) and nearest feature centres (NFC), and it contains two stages. In the first stage, the SFSC classifier computes the feature sphere centroid metric. Then, SFSC obtains the sparse coefficients by solving an L1‐norm minimisation problem and uses the sparse coefficients to calculate the weighted feature sphere centroid distance, which will be utilised for classification. Experiments on the Georgia Tech (GT) face database and AR face database were conducted to evaluate the proposed classifier. The experimental results show that the proposed classifier yields better recognition rate over competing classifiers such as NFC, NFP and SRC. [ABSTRACT FROM AUTHOR]

The developed multispectral imaging system was tested in the current study for its detection accuracy of aflatoxin B1 (AFB1) in single kernel almonds. Based on our previous study, characteristic wavelengths for aflatoxin B1 (AFB1) were selected from the hyperspectral imaging data and a prototype of almond sorter was designed and developed using multispectral imaging system. Five levels of AFB1 concentrations, viz. 0.25, 0.50, 0.75, 1.00 μg/kernel were used for testing of the sorter. Artificial neural network (ANN) was used to predict the AFB1 contamination levels and four discriminant models, viz. support vector machine (SVM), logistic regression (LR), linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were analyzed to classify the contaminated kernels from the normal ones. Results indicated that ANN was very efficient in prediction of AFB1 threshold contamination levels of 0.250 µg/g with accuracy of 99.300%, 98.100%, 95.700%, 86.200% and least error rate of 0.042, 0.077, 0.109 µg/g, 0.187 µg/g respectively for training, cross-validation, prediction and testing using external test set data. The two-class LR model accurately discriminated the contaminated from the noncontaminated almonds with a threshold of 0.25 µg/g and the correct classification rate of 90.800% and 95% for cross-validation and external test datasets, respectively. The multispectral imaging system demonstrated its potential application to rapid online detection of AFB1 contamination levels in single almond kernels and discrimination of contaminated kernels at the same time. • A multispectral imaging system was tested for its accuracy in detection of AFB1 in single kernel almonds. • ANN used for prediction of AFB1 in the almond kernels with R v of 0.98 & RMSEV of 0.077 µg/g. • SVM, LR, LDA, QDA models were developed to classify the control and contaminated kernels. • LR model accurately discriminated the contaminated kernels from the control with CCR of 90.8%. [ABSTRACT FROM AUTHOR]

Of those, 188 patients underwent FESS with MT suture, and 91 patients underwent FESS without MT suture. Keywords: chronic rhinosinusitis; endoscopic sinus surgery; FESS; olfaction; olfactory disorders EN chronic rhinosinusitis endoscopic sinus surgery FESS olfaction olfactory disorders 318 320 3 02/22/22 20220301 NES 220301 INTRODUCTION Functional endoscopic sinus surgery (FESS) is a standard approach for medically treating refractory chronic rhinosinusitis (CRS). [Extracted from the article]

This article contributes to ongoing debate about the effectiveness of information-based policy tools by evaluating environmental information posters using a novel eye-tracking method to examine viewing behavior. Findings from a multi-method study involving 93 students indicate that: (1) slogans are typically the first thing that subjects fixate on when presented with an information poster, (2) recall of poster content is highest when positive slogans and negative images are included, and (3) posters should be targeted to different audiences for maximum effectiveness. These findings indicate that eye-tracking technologies can be incorporated into designing more effective information-based policy instruments by examining behavior. [ABSTRACT FROM AUTHOR]

• Propose a weighted hybrid multi-view fusion method for the semi-supervised classification problem. • Introduce Variant Alternating Splitting Augmented Lagrangian Method to solve the rank consistency problem. • Design an efficient iterative algorithm to optimize the objective function. This paper proposes a weighted hybrid multi-view fusion method for the semi-supervised classification problem. Instead of getting access to the features from different views directly, this method utilizes the square losses of the multi-view classifiers to exploit the between-view relationship, which preserves the privacy of data. Considering the different prediction capability of classifiers on multiple views, an objective function with the constraint of rank consistency is constructed to weight view-specific learners adaptively, where the constraint makes each view-specific learner improve its performance by exploring the predicted results of other learners. Furthermore, an iterative algorithm based on the Variant Alternating Splitting Augmented Lagrangian Method (VASALM) and the quadratic programming method is developed to optimize the objective function. Experimental results on different real-world datasets demonstrate the effectiveness of the proposed method for multi-view learning. The experiments also analyze parameter sensitivity and convergency of the optimization algorithm. [ABSTRACT FROM AUTHOR]

• Multiple particle tracking is challenging in synchrotron X-ray images. • Discriminative appearance and neighbouring topology learning are proposed. • A detection recovery method using multi-frame association is proposed. • Our method achieves tracking errors of 7.03% and association errors of 7.22%. Recent research has introduced a novel method of directly monitoring the effects of potential therapies for Cystic Fibrosis (CF) airway disease by quantifying mucociliary transit (MCT). In this method, micron-sized spherical particles are deposited into rodent airways, and synchrotron X-ray images are obtained to quantify the motion of the particles. However, the accurate tracking of these particles is challenging due to low contrast, image noise, and the presence of overlapping particles. Therefore, this paper proposes a novel method for detecting and tracking circular particles and measuring their dynamics. Accurate particle detection is achieved by applying a convolutional neural network (CNN). For robust multi-object tracking, this paper proposes a confidence model utilizing appearance and neighbouring topology learned by linear discriminant analysis. We also propose a detection recovery method using multi-frame association to restore the missed particles due to overlapping. The proposed method is tested with several different datasets and shows high levels of detection and tracking accuracy. Finally, by offering visual tracking analyses that display merging and splitting events, the proposed method can provide a better understanding of airway MCT behaviour. [ABSTRACT FROM AUTHOR]

• Characteristics of the coke deposits on lamellar metal (Ga or Zn)-modified zeolites were studied. • Mesoporous lamellar structure decreases the coke formation by facilitating the external coke deposition. • Metal modification decreases the coke formation by changing the acidity of zeolite. • Highest fraction of light coke is obtained for Zn-modified lamellar zeolite. • Both zeolite structure and metal-modified acidity affect the coke formation. The effects of meso-/microporous structure and metal-additive (Ga or Zn) of lamellar MFI catalysts on the characteristics of coke deposits during ethylene-to-aromatic liquids conversion were investigated. The nature, composition, and location of coke deposits in spent lamellar catalysts were analyzed and compared to those on the microporous MFI counterparts, using FTIR, UV–Vis, GC–MS, and argon adsorption-desorption. The total amount of coke and the changes in coke nature during catalyst regeneration were studied by MS/FTIR combined with temperature programmed oxidation. The lamellar meso-/microporous structure of MFI reduces the coke quantity and the heavy coke fractions. The coke preferentially deposites on external surface of lamellar zeolite due to the lower diffusion limitation for bulky coke precursors. Metal-additive changes the catalyst acidity and decreases the coke formation rate, especially when zinc is used. Therefore, the coke formation on zeolite can be tuned by modulating the textural and acidity properties of the metal-modified catalyst. [ABSTRACT FROM AUTHOR]

Volcano curves for hydrocarbon total oxidation. • The use of the volcano curve to predict catalysts for an entire homologous series is exploited. • Catalytic activity over seven monometallic and three Ag-Pd/Al 2 O 3 bimetallic catalysts is evaluated experimentally. • Hysteresis in activity, with three distinct kinetic regimes, with varying oxygen concentration is found. • Hydrocarbons with two or more carbon atoms are good surrogates of the alkane homologous series whereas methane is not. • The feed composition controls the catalyst oxidation state and potentially impacts the optimal catalyst properties. Volcano curves are typically developed and used for predicting new catalysts for a single reaction and one substrate. The concept of using the volcano curve to predict catalysts for an entire homologous series of reactions has been unexplored. Herein the catalytic activity of seven monometallic catalysts (Pt, Pd, Rh, Ag, Ni, Cu, and Co/Al 2 O 3) and three Ag-Pd/Al 2 O 3 bimetallic catalysts is evaluated in the total oxidation of small alkanes (methane, ethane, propane, and isobutane) in the 280–400 °C temperature range under fuel lean and rich conditions. We show that hysteresis in activity, with three distinct kinetic regimes, is a common phenomenon of alkane oxidation over all catalysts studied when varying the oxygen concentration, and the size of the hysteresis loop depends on the oxophilicity of the catalyst and the reducing ability of the hydrocarbon. Expectedly, the concept of the universality of the volcano curve for a homologous series is valid but only when a suitable surrogate substrate is chosen. Hydrocarbons with two or more carbon atoms can serve as surrogates of the alkane homologous series, whereas methane is not. Interestingly and consistent with the hysteresis, the feed composition controls the catalyst oxidation state and potentially impacts the optimal catalyst descriptors used to determine new catalysts. The predicted 1:3 Ag-Pd catalyst is indeed superior to single metals for the homologous series under fuel lean conditions for ethane and larger alkanes. It is inferior to Pt under fuel rich conditions and better than Pd and Pt for methane rich conditions. A method for qualitative inference of the catalyst structure, based on the volcano curve and the oxidation state of the catalyst, is proposed. [ABSTRACT FROM AUTHOR]

Analytical CT reconstruction is popular in practice because of its computational efficiency, but it suffers from low reconstruction quality when an insufficient number of projections are used. To address this issue, this paper presents a new analytical method of backprojection Wiener deconvolution (BPWD). BPWD executes backprojection first, and then applies a Wiener deconvolution to the whole backprojected image. The Wiener filter is derived from a ramp filter, enabling the proposed approach to perform reconstruction and denoising simultaneously. The use of a filter after backprojection does not differentiate between real sampled projections and interpolated ones, introducing reconstruction errors. Therefore a weighted ramp filter was applied to increase the contribution of real sampled projections in the reconstruction, thus improving reconstruction quality. Experiments on synthetic data and real phase-contrast x-ray images showed that the proposed approach yields better reconstruction quality compared to the classical filtered backprojection (FBP) method, with comparable reconstruction speed. [ABSTRACT FROM AUTHOR]

• A new DPC algorithm for uneven density datasets is proposed. • A new local density calculation method based on fuzzy neighborhood is designed. • A new allocation strategy based on weighted shared nearest neighbor is proposed. • The new DPC algorithm has excellent clustering accuracy for different types of datasets. Uneven density data refers to data with a certain difference in sample density between clusters. The local density of density peaks clustering algorithm (DPC) does not consider the effect of sample density difference between clusters of uneven density data, which may lead to wrong selection of cluster centers; the algorithm allocation strategy makes it easy to incorrectly allocate samples originally belonging to sparse clusters to dense clusters, which reduces clustering efficiency. In this study, we proposed the density peaks clustering algorithm based on fuzzy and weighted shared neighbor for uneven density datasets (DPC-FWSN). First, a nearest neighbor fuzzy kernel function is obtained by combining K-nearest neighbor and fuzzy neighborhood. Then, local density is redefined by the nearest neighbor fuzzy kernel function. The local density can better characterize the distribution characteristics of the sample by balancing the contribution of sample density in dense and sparse areas, in order to avoid the situation that the sparse cluster does not have a cluster center. Finally, the allocation strategy for weighted shared neighbor similarity is proposed to optimize the sample allocation at the boundary of the sparse cluster. Experiments are performed on IDPC-FA, FKNN-DPC, FNDPC, DPCSA and DPC for uneven density datasets, complex morphologies datasets and real datasets. The clustering results demonstrate that DPC-FWSN effectively handles datasets with uneven density distribution. [ABSTRACT FROM AUTHOR]

Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative citation weight is applied to assess the impact of a scholarly paper. A higher-order weighted quantum PageRank algorithm is also developed to address the behavior of multiple step citation flow. Capturing the citation dynamics with higher-order dependencies reveals the actual impact of papers, including necessary self-citations that are sometimes excluded in prior studies. Quantum PageRank is utilized in this paper to help differentiating nodes whose PageRank values are identical. [ABSTRACT FROM AUTHOR]

A backpressure-based data collecting scheme has been applied in the Internet of Things, which can control the network congestion effectively and increase the network throughput. However, there is an obvious shortcoming in the traditional backpressure data collecting scheme for the network service chain. It attempts to search all possible paths between source node and destination node in the networks, causing an unnecessary long path for data collection, which results in large end-toend delay and redundant energy consumption. To address this shortcoming of backpressure data collecting scheme in the Internet of Things, this article proposes an energy-aware and distance-aware data collecting scheme to enhance the lifetime of backpressure-based data collecting schemes. We propose an energy- and distance-based model that combines the factors of queue backlog, hop counts, and residual energy for making routing decisions. It not only reduces the unnecessary energy consumption, but also balances the residual energy. The experiment results show that the proposed scheme can reduce unnecessary energy consumption and end-to-end delay compared to the traditional and LIFO-based schemes. Meanwhile, it balances the energy of nodes and extends the lifetime of an Internet of Things. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fast-learning image classifier, that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm. We argue that by transferring the use of prior knowledge from the detection and tracking stages to the classification stage, we can design a robust, general purpose object recognition system with the ability to detect and track a variety of object types. We describe our biologically inspired implementation, which adaptively learns the shape and motion of tracked objects, and apply it to the Neovision2 Tower benchmark data set, which contains multiple object types. An experimental evaluation demonstrates that our approach is competitive with the state-of-the-art video object recognition systems that do make use of object-specific prior knowledge in detection and tracking, while providing additional practical advantages by virtue of its generality. [ABSTRACT FROM PUBLISHER]

Scholarly article impact reflects the significance of academic output recognised by academic peers, and it often plays a crucial role in assessing the scientific achievements of researchers, teams, institutions and countries. It is also used for addressing various needs in the academic and scientific arena, such as recruitment decisions, promotions, and funding allocations. This article provides a comprehensive review of recent progresses related to article impact assessment and prediction. The review starts by sharing some insight into the article impact research and outlines current research status. Some core methods and recent progress are presented to outline how article impact metrics and prediction have evolved to consider integrating multiple networks. Key techniques, including statistical analysis, machine learning, data mining and network science, are discussed. In particular, we highlight important applications of each technique in article impact research. Subsequently, we discuss the open issues and challenges of article impact research. At the same time, this review points out some important research directions, including article impact evaluation by considering Conflict of Interest, time and location information, various distributions of scholarly entities, and rising stars. [ABSTRACT FROM AUTHOR]

Cystic Fibrosis is a genetic disease in which the production of thick sticky mucus compromises the mucociliary transit (MCT) system and causes obstruction of the conducting airways. This results in a cycle of inflammation and infection that dramatically reduces quality of life and causes an early death for most. To directly assess airway health and the effects of potential treatments, synchrotron X-ray imaging techniques have been developed to non-invasively quantify MCT, by visualizing the motion of micron-sized spherical particles deposited into the nasal airways of live mice. Since the level of contrast between the target particles and the background is quite low, and the particles often overlap, most existing methods show a low detection accuracy for the MCT tracking particles in these state-of-the-art PCXI images. This paper proposes a new way to automatically detect the circular shapes of micron-sized particles in these low-contrast X-ray images. The proposed algorithm uses a gradient-directional, sectored ring mask, combined with an edge projection into the ring boundary to identify circular shapes. This new algorithm achieves significantly improved marker particle detection rate, 92.1% precision, 93.9% recall and 92.7% F-measurement, compared to existing methods. It can detect a certain degree of overlapping particles that existing methods struggle to achieve. This algorithm provides automatic MCT particle counting, which significantly reduces the manual labelling process for MCT analysis of living animals. [ABSTRACT FROM AUTHOR]

Socially aware networking (SAN) is a new communication paradigm, in which the social characteristics of mobile nodes are exploited to improve the performance of data distribution. In SAN, mobile carriers may exhibit selfish behaviors and refuse to relay messages for others for various reasons, such as limited resources (e.g., buffer, energy, and bandwidth) or social relationships. Several incentive schemes have recently been investigated to stimulate selfish users for cooperation in data forwarding. However, a majority of the existing methods have not fully studied nodes' social relationships in their selfish behaviors. In this paper, we propose a copy adjustable incentive scheme (CAIS), which adopts the virtual credit concept to stimulate selfish nodes to cooperate in data forwarding. In CAIS, we consider a network in which the nodes are divided into certain communities based on their social relationships. Then, we apply two types of credits, i.e., social credit and nonsocial credit, to reward the nodes when they relay data for other nodes inside their community or outsiders, respectively. Based on our mechanism, the number of messages a node can replicate to other nodes is adjusted according to its cooperation level and earned credits. To further improve the performance of CAIS, a single-copy data replication policy is employed, which manages the credit distribution of each node according to its available resources. The results of our extensive experiments using both synthetic and trace-driven simulations illustrate that CAIS copes well with node selfishness in community-based networks and outperforms other benchmark protocols with high data delivery ratio, low communication overhead, and short data delivery latency. [ABSTRACT FROM PUBLISHER]

The synthesis of hierarchical meso-/microporous zeolite materials with spatially controlled morphology, meso-/microporosity, and acidity is an expanding area of research interest for a wide range of applications. Here, we report a one-step dual template synthesis method for integration of 3-dimensional (3D) BEA nanosponge and ultra-thin 2D lamellar MFI into a new type of hierarchical meso-/microporous zeolite composite structures. Specifically, the 2D layered MFI nanosheets were laid over the surface of or interdigitated into the 3D BEA particles in the bulk BEA nanosponge-lamellar MFI (BBLM) zeolite structure, which generated a unique morphology of interconnected micropores and mesopores underneath the ‘skinning’ shell (∼3–10 nm) of MFI nanosheets. The BBLM zeolites have higher mesoporosity than either bare BEA or lamellar MFI zeolites. The micropore size decreases with increasing lamellar MFI component in the composite. The fraction of external acid sites of BBLM zeolite composite, represented by the percentage of active sites accessible to bulky organic base molecules, decreases with increasing MFI component. Additionally, the types of acid sites are diversified in the BBLM composites compared to either bare BEA or lamellar MFI zeolites. The catalysis tests using conversion of benzyl alcohol in mesitylene showed that BBLM zeolites had significant higher activity and durability than single zeolites or their physical mixture. The BBLM zeolite composite provides a good model catalyst with integrated 2D-3D structures and meso-/microporosity for studying a series of important catalytic reactions in hierarchical zeolites. The one-step dual template synthesis method described herein is versatile and facile, which may prove to be a general platform for hierarchical zeolite composite design at the unit-cell scales of zeolites and with potentially broader applicability to other porous materials. [ABSTRACT FROM AUTHOR]

How SARS-CoV-2 penetrates the airway barrier of mucus and periciliary mucins to infect nasal epithelium remains unclear. Using primary nasal epithelial organoid cultures, we found that the virus attaches to motile cilia via the ACE2 receptor. SARS-CoV-2 traverses the mucus layer, using motile cilia as tracks to access the cell body. Depleting cilia blocks infection for SARS-CoV-2 and other respiratory viruses. SARS-CoV-2 progeny attach to airway microvilli 24 h post-infection and trigger formation of apically extended and highly branched microvilli that organize viral egress from the microvilli back into the mucus layer, supporting a model of virus dispersion throughout airway tissue via mucociliary transport. Phosphoproteomics and kinase inhibition reveal that microvillar remodeling is regulated by p21-activated kinases (PAK). Importantly, Omicron variants bind with higher affinity to motile cilia and show accelerated viral entry. Our work suggests that motile cilia, microvilli, and mucociliary-dependent mucus flow are critical for efficient virus replication in nasal epithelia. [Display omitted] • SARS-CoV-2 binds ACE2 on multicilia in airway epithelia immediately upon infection • Depleting motile cilia inhibits viral entry by SARS-CoV-2 and other respiratory viruses • SARS-CoV-2 activates PAK kinases to rearrange airway microvilli driving viral exit • Omicron variants accelerate cilia-dependent entry through the airway mucin barrier Respiratory viruses, including SARS-CoV-2, bypass the defensive mucus/mucin layer of the airway by entering and exiting epithelial cells via their protruding, motile cilia and microvilli. [ABSTRACT FROM AUTHOR]

This paper presents a bibliographic analysis of Nature articles based on altmetrics. We assess the concern degree of social users on the Nature articles through the coverage analysis of Twitter and Facebook by publication year and discipline. The social media impact of a Nature article is examined by evaluating the mention rates on Twitter and on Facebook. Moreover, the correlation between tweets and citations is analyzed by publication year, discipline and Twitter user type to explore factors affecting the correlation. The results show that Twitter users have a higher concern degree on Nature articles than Facebook users, and Nature articles have higher and faster-growing impact on Twitter than on Facebook. The results also show that tweets and citations are somewhat related, and they mostly measure different types of impact. In addition, the correlation between tweets and citations highly depends on publication year, discipline and Twitter user type. [ABSTRACT FROM AUTHOR]