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The current version of the Declaration of Helsinki states that ‘the benefits, risks, burdens and effectiveness of a new intervention must be tested against those of the best current proven intervention(s) … ’. This wording implies that it is acceptable for patients to be assigned to receive an unproven new intervention and to be denied a best current proven intervention. We assert that patients being invited to participate in controlled trials cannot, ethically, be expected to forego proven beneficial forms of care. Patients being treated in controlled trials should not knowingly be disadvantaged compared with similar patients being treated in usual clinical care, where they have access to beneficial care. In this article, we have tried to separate for discussion ‘the withholding of effective care from trial participants’, ‘informed consent to treatment’, ‘blinding’ and ‘use of placebos’.

To assess the prevalence of abortion among population groups and changes in rates between 2008 and 2014.We used secondary data from the Abortion Patient Survey, the American Community Survey, and the National Survey of Family Growth to estimate abortion rates. We used information from the Abortion Patient Survey to estimate the lifetime incidence of abortion.Between 2008 and 2014, the abortion rate declined 25%, from 19.4 to 14.6 per 1000 women aged 15 to 44 years. The abortion rate for adolescents aged 15 to 19 years declined 46%, the largest of any group. Abortion rates declined for all racial and ethnic groups but were larger for non-White women than for non-Hispanic White women. Although the abortion rate decreased 26% for women with incomes less than 100% of the federal poverty level, this population had the highest abortion rate of all the groups examined: 36.6. If the 2014 age-specific abortion rates prevail, 24% of women aged 15 to 44 years in that year will have an abortion by age 45 years.The decline in abortion was not uniform across all population groups.

Recent years have seen a paradigm shift in the management of patients with diabetes mellitus. Rather than good glycaemic control being the sole primary aim, the therapeutic focus has broadened to consider potential additional cardiovascular and renal benefits. Sodium-glucose co-transporter 2 inhibitors, such as empagliflozin, canagliflozin and dapagliflozin, have gained increasing prominence, with evidence suggesting significant improvement in outcomes in patients with established cardiovascular and renal disease. Here, we discuss the benefits and relative risks of these novel agents and highlight important clinical issues of relevance to general physicians.

Objective: To study the relationship between consumption of milk and milk products, calcium, lactose and vitamin D and occurrence of colorectal cancers. Design: Prospective cohort study. Subjects: A total of 9959 men and women aged 15 y or older without history of cancer at baseline. During a 24 y follow-up, 72 new cancers of the large bowel (38 in the colon and 34 in the rectum) were detected. Results: Consumption of milk and total milk products was suggested to be inversely related to colon cancer incidence, whereas no similar association was seen for rectal cancer. The relative risk between the highest and lowest quartiles of intake adjusted for potential confounding factors was 0.46 (95% confidence interval 0.14–1.46, P for trend 0.09) for milk and 0.37 (95% CI=0.12–1.39, P for trend 0.06) for total milk products. Lactose intake showed a similar inverse relationship with colon cancer: the relative risk was 0.31 (95% CI=0.08–1.15, P for trend 0.03). Intake of vitamin D or total dietary calcium was not significantly related to colorectal cancer risk, whereas calcium provided by fermented milk products was associated with increased colorectal cancer incidence; in the highest quartile the multivariate adjusted relative risk for colorectal cancer was 2.07 (95% CI=1.00–4.28). Conclusions: Our results indicate that individuals showing high consumption of milk have a potentially reduced risk of colon cancer; however, the association does not appear to be due to intake of calcium, vitamin D, or to specific effects of fermented milk. Sponsorship: This study was supported by a grant from the Swedish Cancer Foundation. European Journal of Clinical Nutrition (2001) 55, 1000–1007

Objective: To demonstrate sexual dimorphism in serum leptin levels not only during puberty, but also in childhood in Japan. Design: Cross-sectional study. Setting: Hamamatsu-Hokuen study in Japan. Subjects: Body weight and height were measured in normal-weight Japanese children and adolescents (143 boys, 178 girls), and 161 boys and 129 girls whose percentage of overweight for the standard (%Wt) was more than+25%. Serum leptin levels were compared with %Wt. Subjects were divided into group 1 (6–10 y of age) and group 2 (11–15 y of age) according to their age. Results: In overweight subjects, leptin was more highly correlated with %Wt in boys of group 2 (r=0.67, P

Sex differences are commonly observed in behaviors that are closely linked to adaptive function, but sex differences can also be observed in behavioral "building blocks" such as locomotor activity and reward processing. Modern neuroscientific inquiry, in pursuit of generalizable principles of functioning across sexes, has often ignored these more subtle sex differences in behavioral building blocks that may result from differences in these behavioral building blocks. A frequent assumption is that there is a default (often male) way to perform a behavior. This approach misses fundamental drivers of individual variability within and between sexes. Incomplete behavioral descriptions of both sexes can lead to an overreliance on reduced "single-variable" readouts of complex behaviors, the design of which may be based on male-biased samples. Here, we advocate that the incorporation of new machine-learning tools for collecting and analyzing multimodal "big behavior" data allows for a more holistic and richer approach to the quantification of behavior in both sexes. These new tools make behavioral description more robust and replicable across laboratories and species, and may open up new lines of neuroscientific inquiry by facilitating the discovery of novel behavioral states. Having more accurate measures of behavioral diversity in males and females could serve as a hypothesis generator for where and when we should look in the brain for meaningful neural differences.

OBJECTIVES: Following the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and the subsequent global spread of the 2019 novel coronavirus disease (COVID-19), health systems and the populations who use them have faced unprecedented challenges. We aimed to measure the impact of COVID-19 on the uptake of hospital-based care at a national level. DESIGN: The study period (weeks ending 5 January to 28 June 2020) encompassed the pandemic announcement by the World Health Organization and the initiation of the UK lockdown. We undertook an interrupted time-series analysis to evaluate the impact of these events on hospital services at a national level and across demographics, clinical specialties and National Health Service Health Boards. SETTING: Scotland, UK. PARTICIPANTS: Patients receiving hospital care from National Health Service Scotland. MAIN OUTCOME MEASURES: Accident and emergency (A&E) attendances, and emergency and planned hospital admissions measured using the relative change of weekly counts in 2020 to the averaged counts for equivalent weeks in 2018 and 2019. RESULTS: Before the pandemic announcement, the uptake of hospital care was largely consistent with historical levels. This was followed by sharp drops in all outcomes until UK lockdown, where activity began to steadily increase. This time-period saw an average reduction of −40.7% (95% confidence interval [CI]: −47.7 to −33.7) in A&E attendances, −25.8% (95% CI: −31.1 to −20.4) in emergency hospital admissions and −60.9% (95% CI: −66.1 to −55.7) in planned hospital admissions, in comparison to the 2018–2019 averages. All subgroup trends were broadly consistent within outcomes, but with notable variations across age groups, specialties and geography. CONCLUSIONS: COVID-19 has had a profoundly disruptive impact on hospital-based care across National Health Service Scotland. This has likely led to an adverse effect on non-COVID-19-related illnesses, increasing the possibility of potentially avoidable morbidity and mortality. Further research is required to elucidate these impacts.

This overview of the molecular pathology of lung cancer includes a review of the most salient molecular alterations of the genome, transcriptome, and the epigenome. The insights provided by the growing use of next-generation sequencing (NGS) in lung cancer will be discussed, and interrelated concepts such as intertumor heterogeneity, intratumor heterogeneity, tumor mutational burden, and the advent of liquid biopsy will be explored. Moreover, this work describes how the evolving field of molecular pathology refines the understanding of different histologic phenotypes of non-small-cell lung cancer (NSCLC) and the underlying biology of small-cell lung cancer. This review will provide an appreciation for how ongoing scientific findings and technologic advances in molecular pathology are crucial for development of biomarkers, therapeutic agents, clinical trials, and ultimately improved patient care.

Aims: To determine the efficacy of XPro1595 to improve pathophysiological and functional outcomes in a mouse model of traumatic brain injury (TBI). Background: Symptoms associated with TBI can be debilitating, and treatment without off-target side effects remains a challenge. This study aimed to investigate the efficacy of selectively inhibiting the soluble form of TNF (solTNF) using the biologic XPro1595 in a mouse model of TBI. Objectives: Use XPro1595 to determine whether injury-induced solTNF promotes hippocampal inflammation and dendritic plasticity and associated functional impairments. Methods: Mild-to-moderate traumatic brain injury (CCI model) was induced in adult male C57Bl/6J WT and Thy1-YFPH mice, with XPro1595 (10 mg/kg, S.C.) or vehicle being administered in a clinically relevant window (60 minutes post-injury). The animals were assessed for differences in neurological function, and hippocampal tissue was analyzed for inflammation and glial reactivity, as well as neuronal degeneration and plasticity. Results: We report that unilateral CCI over the right parietal cortex in mice promoted deficits in learning and memory, depressive-like behavior, and neuropathic pain. Using immunohistochemical and Western blotting techniques, we observed the cortical injury promoted a set of expected pathophysiology’s within the hippocampus consistent with the observed neurological outcomes, including glial reactivity, enhanced neuronal dendritic degeneration (dendritic beading), and reduced synaptic plasticity (spine density and PSD-95 expression) within the DG and CA1 region of the hippocampus, that were prevented in mice treated with XPro1595. Conclusion: Overall, we observed that selectively inhibiting solTNF using XPro1595 improved the pathophysiological and neurological sequelae of brain-injured mice, which provides support for its use in patients with TBI.

China is the most productive seaweed farming country in the world and her seaweed imports and exports have a significant impact on global seaweed trade commodities and food security. Nevertheless, few studies had delved into the main characteristics and development of China's seaweed farming industry. This paper aims to narrow this research gap by analyzing trade patterns in China's seaweed products and the international competitiveness of seaweed product by using the international market share index (IMS), the trade competitiveness index (TC), and revealed comparative advantage index (RCA) from 2002 to 2017. The results showed that Japan, the Association of Southeast Asian Nations (ASEAN), Chile, Peru, and the Republic of Korea are China's main trade partners, the total trade value of China's seaweed products has grown rapidly, its imports have gradually exceeded exports, the trade deficit continues to expand, and its competitiveness keeps decreasing. The reasons for this trend may include the changing seaweed trade commodity structure, product differentiation, increased government support in competing countries, and trade barriers among the trade partners. We propose actively expanding international trade markets, establishing a strong seaweed product processing industry to develop high value-added seaweed products, optimizing the trade commodity structure, and differentiating of seaweed products to improve the competitiveness of China's seaweed products.

Using a continuous-time model of litigation, we show that the increasingly popular practice of third-party litigation financing has ambiguous welfare implications. A defendant and a plaintiff bargain over a settlement payment. The defendant takes costly actions to avoid deadweight losses associated with large transfers to the plaintiff. Litigation financing bolsters the plaintiff, leading to larger deadweight losses. However, by endogenously deterring the defendant from taking costly actions, litigation financing can nonetheless improve the joint surplus of the plaintiff and the defendant. In contrast to popular opinion, litigation financing does not necessarily encourage high-risk frivolous lawsuits.

Given the alleged uniqueness of Islamic stocks, it is expected that they should provide insurance when faced with adverse market conditions. This expectation is tested by assessing contagion, using 25 Islamic indexes during the period 2007–2017, by employing contemporary econometric techniques. The results reveal robust contagion effects of the financial crisis on Islamic stock indexes. Furthermore, we find Baker and Wurgler’s investor sentiment can predict Islamic stock returns during the crisis period. Our findings indicate that Islamic stocks cannot be used as a haven asset during financial turmoil.

Shariah screening discards the firms that belong to impermissible business sectors (or sin industries) and follow capital structure with high debt and current assets. This study tests whether the firms passing Shariah screening have better (or worse) governance quality as compared to firms not subjected to Islamic screening. The screened firms may have lesser governance quality as they cannot use debt to discipline managers or achieve optimal capital structure. On the contrary, they may be better governed as these firms get higher presence of institutional investors and better analyst coverage. This paper provides comparison of governance quality of Shariah compliant (SC) firms in United States by using proprietary dataset of Dow Jones US Indices. The screened firms offer ground for a natural experiment as they pass negative ethical screening and meet financial criteria for the inclusion in the index. The findings suggest that the SC firms have lesser governance quality than Shariah Non-Compliant firms. The lower level of governance can be attributed to lower Size, lower Profitability, higher Dividend Payout, higher Total Risk and lower Free Cash Flow. Various robustness tests are performed to validate the findings and the results remained robust. These findings provide useful insights about the governance mechanism of SC firms that are emerging as an important alternative investment class in the last two decades.

Mediterranean mussel farming in Greece developed considerably during the last 40 years reaching a gross commodity product up to the limits of the country's production capacity (35–40,000 tonnes/year). Despite the achievements in the sector's growth, little or no effort has been attributed yet to risk assessment and moreover to risk management of the activity. The present effort aims at developing a working framework for the shellfish aquaculture of Greece to be used as a tool by the sector's decision makers to advance strategies for risk elimination or avoidance. The work was based on a generic risk management standard tool, the Joint Australian and New Zealand Risk Management Standard AS/NZS ISO 31000:2009 that has been adapted to the specific national characteristics of all levels of the mussel farming business -activities and the industry function. The framework supported by data sets regarding development, production, profits and losses, retrieved by surveys through distributed questionnaires or interviews during site-visits, as well as by collecting data from national and international authorities. Data input covered technology, farm size, farmer risk-attitude, risk-management strategies, risk-perceptions and socioeconomic profiles. Major risks and risk management options were identified providing aid for remediation risk policies to the stakeholders.

To overcome the cost of competition resulting from close social proximity while foraging in a group, individuals may balance their use of private (i.e. acquired from personal sampling) and social (i.e. acquired by watching other individuals) information in order to adjust their foraging strategy accordingly. Reliability of private information about environmental characteristics, such as the spatial distribution of prey, is thus likely to affect individual movement and social interactions during foraging. Our aim was to investigate how movement characteristics of foraging individuals changed as they acquired reliable private information about the spatial occurrence of prey in a foraging context. We allowed guppies (Poecilia reticulata) to develop the reliability of their private knowledge about prey spatial occurrence by repeatedly testing shoals in a foraging task under three experimental distributions of prey: 1) aggregated prey forming three patches located in fixed locations, 2) scattered distribution of prey with random locations, or 3) no prey (used as control). We then applied tracking methods to obtain individual time series of spatial coordinates from which we computed a suite of movement variables reflecting search effort, social proximity and locomotion characteristics during foraging, in order to examine changes occurring over repeated trials and to investigate which best explained foraging success. We show that foraging shoals became more efficient at finding and consuming food over the first three days by increasing their time spent active. Over time, individuals foraging on either scattered or aggregated prey travelled greater distances, showed an increasing distance to their closest neighbour and became slightly more stochastic in their acceleration profile, compared to control individuals. We found that behaviour changed as private information increased over time. Social proximity was the major predictor of foraging success in the absence of prior foraging information, while stochasticity in acceleration and search effort became the most important predictors of foraging success as information increased. In conclusion, we show that individual movement patterns changed as they acquire private information. Contrary to our predictions, the spatial distribution of prey did not affect any of the movement variables of interest. Our results emphasise the importance of information, both private and social, in shaping movement behaviour in animals. Keywords: social foraging, movement, private information, prey spatial distribution, fish.

There is a continuing interest in exploring the impact of operational excellence (OE) on operational performance. Several OE practices such as Lean, Agile, and Six Sigma are well recognized. However, not all OE deployments in firms have been successful, and a failure of such efforts has often been expensive. Past research reveals several critical failure factors (CFFs) that lead to OE deployment failures in firms. We present these CFFs as an integrated model, based on two dominant schools of OE that promote technical and behavioral factors independently. Further, we validate their direct and mediating relationships through an empirical examination of 663 responses collected from 153 manufacturing units across the USA, U.K., China, and India. This article contributes to the OE body of knowledge by examining the significant direct and mediating effects of behavioral and technical CFFs on the OE failures. Our findings reveal that the technical CFFs mediate the impact of behavioral CFFs on OE failures. Consequently, several managerial and theoretical implications are presented.

Summarization: Alternative tourism has gained considerable interest among consumers and enterprises in the tourism sector, creating new opportunities for providing high quality and innovative tourist services, while contributing to sustainable development. The Internet plays a key role as a tool for promoting alternative tourism. Motivated by this, this article presents an original research on the evaluation of the content features of the websites of enterprises involved with alternative tourism services in the region of Chania, Greece. The sample consists of 28 websites evaluated over 11 performance criteria through the ELECTRE III multicriteria method. The websites are ranked in a benchmarking context and the results of the evaluation are used to identify the most successful practices, as well as the website features that require improvements for the enterprises to take advantage of the opportunities that arise in the new era of technological innovation in the tourism sector. Presented on: IEEE Transactions on Engineering Management

Purpose To describe the use of glycerine in improving media clarity in cases with edematous cornea. Methods Retrospective case-series including patients with posterior segment pathologies needing surgical invention and having corneal edema. Each case was studied for the role of topical application of glycerine instead of viscoelastic agents and the course of surgery. The cases were followed up for minimum 3-months duration. Results Six cases with corneal edema having posterior segment pathology underwent surgery with intraoperative topical application of glycerine. The corneal edema was seen to clear with progression of surgery and was maintained until the end of surgery. Procedures like vitreoretinal surgery, identification of break, internal limiting membrane peeling, intraocular lens explantation, scleral indentation, DSEK graft removal, and subretinal band removal could be performed in these cases. Conclusion Intraoperative glycerine use during vitreoretinal surgeries is helpful in improving the corneal clarity and maintaining it till the end of surgery.

Diagnostic theories are fundamental to information system (IS) practice and are represented as trees. While there are approaches for validating diagnostic trees, these validate the overall performance of the tree rather than identifying ways incorrect diagnoses can occur. It is important to fully validate diagnostic trees because even if the tree gives the correct decision “most of the time,” it is possible for incorrect decisions traveling down little-used branches of the tree to result in catastrophic decisions. In this article, we describe the process of using a variant of q-sorting to validate diagnostic trees. In this methodology, diagnostic trees that independent experts develop are transformed into a quantitative form, and that quantitative form is tested to determine the inter-rater reliability of the individual branches in the tree. The trees are then successively transformed to incrementally test if they branch in the same way. The results help researchers not only identify quality items for use in a diagnostic tree but also facilitate diagnoses of problems with those items and facilitate the reconciliation of discrepant trees by experts. The methodology validates not only the whole tree but also its subparts.

Millimeter wave components, such as circulators and isolators, frequently use magnetic fields to break symmetry of the signal propagation and provide unidirectional signal transmission. While effective, these components have not seen the level of miniaturization of other millimeter wave components, primarily due to the discrete nature of the magnets used in the components. Using circulators in the 40-50 GHz range as a motivating application, requirements arise for the deposited films, namely immunity to eddy currents, sufficient magnetization to act as self-biasing magnets, and out-of-plane orientation of the self-biasing field. Based on these required properties, hexaferrite materials are selected for their strong magnetocrystalline anisotropy (MCA) and low conductance. The difficulty of integrating these components monolithically with monolithic microwave integrated circuits (MMIC) originates from the incompatibility of crystal structure with standard semiconductor materials and process conditions. Additive manufacturing using a composite of strontium hexaferrite (SrFe12O19) particles and photoresist has been chosen as a method to overcome the difficulties of integrating hexaferrite material to semiconductor substrates. Due to their large internal anisotropy field, the particles of strontium hexaferrite tend to rotate to the field direction instead of changing magnetization direction under application of an external magnetic field (less than the anisotropy field). We have developed a method for 3D printing composites of high strontium hexaferrite concentration (up to 20% by volume) in a liquid photoresist, SU8. Rotation of hexaferrite particles in polymer matrix and thus magnetic anisotropy has been demonstrated in the composite, which is subsequently cured to hold the physical position and orientation of the particles. The anisotropy of the self-biasing field provided by the films has been experimentally characterized, and a ferromagnetic resonance (FMR) frequency ~43 GHz has been observed. We have also characterized the viscosity of the particle-laden polymer at different particle concentrations. 3D printing of this composite with poling will make it possible to directly print magnetic components that require out-of-plane anisotropic magnetization.

Knowledge graph embedding models have gained significant attention in AI research. The aim of knowledge graph embedding is to embed the graphs into a vector space in which the structure of the graph is preserved. Recent works have shown that the inclusion of background knowledge, such as logical rules, can improve the performance of embeddings in downstream machine learning tasks. However, so far, most existing models do not allow the inclusion of rules. We address the challenge of including rules and present a new neural based embedding model (LogicENN). We prove that LogicENN can learn every ground truth of encoded rules in a knowledge graph. To the best of our knowledge, this has not been proved so far for the neural based family of embedding models. Moreover, we derive formulae for the inclusion of various rules, including (anti-)symmetric, inverse, irreflexive and transitive, implication, composition, equivalence, and negation. Our formulation allows avoiding grounding for implication and equivalence relations. Our experiments show that LogicENN outperforms the existing models in link prediction.

Objective The objective was to develop a novel scoring system that would be predictive of postoperative pulmonary complications in critically ill patients after cardiac and major vascular surgery. Methods A total of 17,433 postoperative patients after coronary artery bypass graft, valve, or thoracic aorta repair surgery admitted to the cardiovascular intensive care units at Cleveland Clinic Main Campus from 2009 to 2015. The primary outcome was the composite of postoperative pulmonary complications, including pneumonia, prolonged postoperative mechanical ventilation (>48 hours), or reintubation occurring during the hospital stay. Elastic net logistic regression was used on the training subset to build a prediction model that included perioperative predictors. Five-fold cross-validation was used to select an appropriate subset of the predictors. The predictive efficacy was assessed with calibration and discrimination statistics. Post hoc, of 13,353 adult patients, we tested the clinical usefulness of our risk prediction model on 12,956 patients who underwent surgery from 2015 to 2019. Results Postoperative pulmonary complications were observed in 1669 patients (9.6%). A prediction model that included baseline and demographic risk factors along with perioperative predictors had a C-statistic of 0.87 (95% confidence interval, 0.86-0.88), with a corrected Brier score of 0.06. Our prediction model maintains satisfactory discrimination (C-statistics of 0.87) and calibration (Brier score of 0.07) abilities when evaluated on an independent dataset of 12,843 recent adult patients who underwent cardiovascular surgery. Conclusions A novel prediction nomogram accurately predicted postoperative pulmonary complications after major cardiac and vascular surgery. Intensivists may use these predictors to allow for proactive and preventative interventions in this patient population.

The body responds to changing circumstances and environmental threats both consciously and subconsciously. The cognitive response to a physical threat normally involves movement mediated by skeletal muscle. There are a number of control mechanisms ‘hardwired’ into the nervous system which enable muscle systems to respond in an integrated fashion without involving a conscious decision, although the subject is usually conscious of what has happened. These include the stretch reflex, the withdrawal reflex and the crossed extensor reflexes. Muscle spindles, Golgi tendon organs and cutaneous nociceptors provide the sensory input to these reflexes, and muscle spindles also play a role in the control of voluntary movement. The autonomic nervous system controls the internal environment in response to environmental change. It consists of the parasympathetic division, which controls basal and vegetative mechanisms, and the sympathetic nervous system, which controls visceral adaptive responses to any sort of environmental change or threat.

Magnetic circuit components have long been the largest and most difficult components to miniaturize. Printed circuit board (PCB) fabrication methods cannot achieve small diameter, high aspect-ratio vias for high winding turn numbers to achieve high inductance, and microelectronics methods cannot achieve the high-quality and thick ferrite core materials. In this paper, we present an alternative breakthrough method of printed circuit fabrication to significantly reduce the effective via diameter for embedded magnetic devices, boosting the inductance per unit area. To reduce the effective via diameter, high-density via plugs are ex-situ fabricated and shaped, and then embedded into PCB substrate in the same process as standard magnetic core embedding. The structure of the plug is such that precise placement within the substrate, or alignment to the plug with the winding pattern, is not necessary. Devices presented in this paper use via plugs with an effective diameter of 40 μm and a theoretically unlimited aspect ratio, though refinements in the plug fabrication process are expected to reduce the via diameter down to 10μm. The process is experimentally demonstrated with a 14-turn racetrack shaped transformer; novel diagnostic methods using magneto-optic garnet films to image current paths are also demonstrated.

In this paper, we propose to tackle egocentric action recognition by suppressing background distractors and enhancing action-relevant interactions. The existing approaches usually utilize two independent branches to recognize egocentric actions, i.e., a verb branch and a noun branch. However, the mechanism to suppress distracting objects and exploit local human-object correlations is missing. To this end, we introduce two extra sources of information, i.e., the candidate objects' spatial location and their discriminative features, to enable concentration on the occurring interactions. We design a Symbiotic Attention withObject-centric featureAlignmentframework (SAOA) to provide meticulous reasoning between the actor and the environment. First, we introduce an object-centric feature alignment method to inject the local object features to the verb branch and noun branch. Second, we propose a symbiotic attention mechanism to encourage the mutual interaction between the two branches and select the most action-relevant candidates for classification. The framework benefits from the communication among the verb branch, the noun branch, and the local object information. Experiments based on different backbones and modalities demonstrate the effectiveness of our method. Notably, our framework achieves the state-of-the-art on the largest egocentric video dataset.

The development of technology has made it easier for engineers to design and test models that allow simulation of real-time water distribution networks with greater accuracy. However, with so many nodes and links in a network, building a model still requires some simplification. One such simplification is the ‘conservative approach’, which applies the principle of ‘lumped demand’, taking the demand only from nodes at the ends of pipes. Herein, the full effect of lumped demand on key water parameters is analysed, on a large-scale network based on as-built networks of Al Furjan and Dubai Silicon Oasis, Dubai, UAE for different conditions. Epanet and WDNetXL software are used for the analysis, and results show the impact of different levels of skeletonisation on the head and velocity values for the two models. The analysis indicates that the head changes are high for a branched network under the extreme condition of firefighting. It includes the effect of skeletonising local tanks, with changes being higher when all tanks are empty. These findings provide a critical evaluation of the performance of this method for the Middle East region and it is concluded that the considerable velocity changes observed in the models could lead to overdesign.

Recent years have witnessed a tremendous increasing of first-person videos captured by wearable devices. Such videos record information from different perspectives than the traditional third-person view, and thus show a wide range of potential usages. However, techniques for analyzing videos from different views can be fundamentally different, not to mention co-analyzing on both views to explore the shared information. In this paper, we take the challenge of cross-view video co-analysis and deliver a novel learning-based method. At the core of our method is the notion of "joint attention", indicating the shared attention regions that link the corresponding views, and eventually guide the shared representation learning across views. To this end, we propose a multi-branch deep network, which extracts cross-view joint attention and shared representation from static frames with spatial constraints, in a self-supervised and simultaneous manner. In addition, by incorporating the temporal transition model of the joint attention, we obtain spatial-temporal joint attention that can robustly capture the essential information extending through time. Our method outperforms the state-of-the-art on the standard cross-view video matching tasks on public datasets. Furthermore, we demonstrate how the learnt joint information can benefit various applications through a set of qualitative and quantitative experiments.

Google Docs is a widely used online word processing software. Despite its broad popularity in business and education, Google Docs is under-utilised as a tool to facilitate qualitative interviews within research. In this article, we reflect on our experiences as two PhDs using Google Docs to conduct synchronous, online, written interviews. We present two case studies, which, to our knowledge, are the first to utilise Google Docs to conduct web-based written interviews. In doing so, we (a) outline the development and implementation of the methodology, (b) highlight the key themes we identified when considering the benefits and challenges of conducting interviews using this technology and (c) discuss possible future uses of the methodology. We argue that synchronous web-based written interviews via Google Docs offer unprecedented opportunities for qualitative research.

Privacy concerns of users threaten the usage of online social networks (OSN). In this regard, privacy preserving of OSN emerged as a convincing solution for preserving the privacy of users and uncovering useful insights from the social network data. In this article, we propose a novel algorithm based on the fuzzy sets and rewiring algorithm for preserving the privacy of users. This article presents the algorithm called privacy-preserving rewiring algorithm (PPRA), which can be used for anonymizing the social network data. The algorithm is validated by showing its effectiveness on four real-world datasets across three major graph mining tasks. The proposed PPRA algorithm will help in preserving the privacy of users in the OSN graph while simultaneously maintaining the utility that can be generated from the OSN graph structure.

BioSentinel is the first biological CubeSat designed and developed for deep space. The main objectives of this NASA mission are to assess the effects of deep space radiation on biological systems and to engineer a CubeSat platform that can autonomously support and gather data from model organisms hundreds of thousands of kilometers from Earth. The articles in this special collection describe the extensive optimization of the biological payload system performed in preparation for this long-duration deep space mission. In this study, we briefly introduce BioSentinel and provide a glimpse into its technical and conceptual heritage by detailing the evolution of the science, subsystems, and capabilities of NASA's previous biological CubeSats. This introduction is not intended as an exhaustive review of CubeSat missions, but rather provides insight into the unique optimization parameters, science, and technology of those few that employ biological model systems.

This briefing provides a short introduction to a supplement of the Ciria Manual on Scour at Bridges and Other Hydraulic Structures published in 2021. The supplement captures additional knowledge since the scour manual was published in 2015. This note is intended for designers and asset managers of structures in the water environment that may be subject to scour.

Background: Beta blockers, mainly propranalol, are usually administered to control heart rate in patients with thyrotoxicosis, especially when congestive heart failure presents. However, when thyrotoxicosis is not controlled, heart rate may be difficult to control even with maximal doses of propranolol. This presentation alerts physicians to the possibility of using ivabradine, a selective inhibitor of the sinoatrial pacemaker, for the control of heart rate. Case presentation: We present a 37-year-old woman with thyrotoxicosis and congestive heart failure whose heart rate was not controlled with a maximal dose of beta blockers during a thyroid storm. The addition of ivabradine, a selective inhibitor of the sinoatrial pacemaker, controlled her heart rate within 48 hours. Conclusion: Ivabradine should be considered in patients with thyrotoxicosis, including those with heart failure, in whom beta blockers are insufficient to control heart rate

Providing a structured approach for complex product development (PD) is a challenging issue that necessitates utilizing sophisticated modeling tools and analysis techniques. One effective approach for optimizing the complex engineering system development is the cross application of modularization and sequencing analyses on the design structure matrix (DSM), which leads to a cost-effective and time-efficient PD process. In this regard, the current study presents an application-specific method for the simultaneous implementation of modularization and sequencing analyses on DSMs to find the most independent and excluded modules with the minimum feedback loops among them. To this end, we first formulate the total feedback length among the modules by introducing two new modules’ feedback criteria. Second, we propose a novel objective function combining these feedback criteria with the modularity index metric to simultaneously fulfill the sequencing and modularization goals. This objective function makes the proposed method application specific in the sense that the expert is able to adjust the importance weight of each criterion based on the project's characteristics. Third, an efficient metaheuristic algorithm named discrete particle swarm optimization simulated annealing (DPSOSA) is developed to find the optimal solution by minimizing the introduced objective function. Eventually, to evaluate the DPSOSA performance in different applications, we conduct comprehensive experiments on a total of 21 well-known real-world DSMs. The obtained results demonstrate the superiority of the proposed method over previous approaches proving its effectiveness in each of modularization, sequencing, and modularization-sequencing experiments.

Small satellite technologies, particularly CubeSats, are enabling breakthrough research in space. Over the past 15 years, NASA Ames Research Center has developed and flown half a dozen biological CubeSats in low Earth orbit (LEO) to conduct space biology and astrobiology research investigating the effects of the space environment on microbiological organisms. These studies of the impacts of radiation and reduced gravity on cellular processes include dose-dependent interactions with antimicrobial drugs, measurements of gene expression and signaling, and assessment of radiation damage. BioSentinel, the newest addition to this series, will be the first deep space biological CubeSat, its heliocentric orbit extending far beyond the radiation-shielded environment of low Earth orbit. BioSentinel's 4U biosensing payload, the first living biology space experiment ever conducted beyond the Earth-Moon system, will use a microbial bioassay to assess repair of radiation-induced DNA damage in eukaryotic cells over a duration of 6-12 months. Part of a special collection of articles focused on BioSentinel and its science mission, this article describes the design, development, and testing of the biosensing payload's microfluidics and optical systems, highlighting improvements relative to previous CubeSat life-support and bioanalytical measurement technologies.

OBJECTIVES: This study was conducted to assess poultry farmers’ knowledge and practices regarding antibiotics, antimicrobial usage (AMU), and antimicrobial resistance (AMR), and to identify the sociodemographic factors of inappropriate use of antibiotics in commercial poultry farms in Bangladesh. METHODS: A qualitative survey of 140 farmers in Bangladesh was conducted from March to May 2019. A logistic regression model was used to identify factors associated with the inappropriate use of antibiotics. RESULTS: 47.1% of farmers were unable to explain antibiotics, 42.9% used antibiotics for preventive purposes, 4.3% used them as growth promoters, 25.7% used them as suggested by veterinarians, 42.9% used leftover antibiotics, 50% did not maintain antibiotics residual withdrawal period, and 98.6% did not know about AMR. In bivariable regression analysis, sex and primary occupation of poultry farmers, their knowledge about withdrawal periods for antibiotics, and no contact with veterinary surgeons (VS) were found to be significantly associated with the inappropriate use of antibiotics, while only ‘no contact with VS’ was identified in multivariable regression analysis. CONCLUSIONS: The findings suggest an urgent need to improve understanding of antibiotics and AMR. Adequate supervision by veterinarians would ensure adherence to appropriate AMU patterns, and would limit the misuse of antibiotics and associated AMR development in farms.