Sinusoidal growth, recruitment, mortality, yield-per-recruit analysis of Buried fan scallop Mimachlamys funebris (Reeve, 1853) and their implications for mariculture

This study described the growth, mortality, recruitment pattern and exploitation rate of the Buried fan scallop (Mimachlamys funebris) in Asid Gulf, Philippines. Monthly length-frequency data (N=3988) from April 2018 to March 2019 were used to examine population parameters using FISAT II. Two estimates of natural mortalities were used to compare variability of limit exploitation rates. Modelling through the oscillating von Bertalanffy growth function revealed that the species is fast growing (K=1.1 year–1) attaining SH∞ of 10.5 cm. Adequacy in the use of the sinusoidal version of the growth formula hinges on the mean annual temperature difference reported in the gulf to be 2°C. Recruitment pattern was continuous and bimodal throughout the year with two high pulses in April–May and September consistent with the reproductive seasonality reported for congeneric species. Fishing mortality coefficients (4.26 and 4.82 year–1) were higher than the natural mortality coefficients (0.543 and 1.1 year–1). Yield and biomass-per-recruit analysis showed that the current exploitation rates are 112% (Ecurr1 = 0.90) and 92% (Ecurr2 = 0.80) higher than the biological reference points adopted for the study particularly E50. These results demonstrate that M. funebris stock is overexploited, which necessitates effective management measures including mariculture

Environmental Control of Annual Reproductive Cycle and Spawning Rhythmicity of Spinefoots

Proceedins of 8th Kuroshio University League Network Formation Toward the Sustainable Society in Kuroshio Region Through Cross-Boader Educatio

A Novel Autoencoder-Based Diagnostic System for Early Assessment of Lung Cancer

© 2018 IEEE. A novel framework for the classification of lung nodules using computed tomography (CT) scans is proposed in this paper. To get an accurate diagnosis of the detected lung nodules, the proposed framework integrates the following two groups of features: (i) appearance features that is modeled using higher-order Markov Gibbs random field (MGRF)-model that has the ability to describe the spatial inhomogeneities inside the lung nodule; and (ii) geometric features that describe the shape geometry of the lung nodules. The novelty of this paper is to accurately model the appearance of the detected lung nodules using a new developed 7th-order MGRF model that has the ability to model the existing spatial inhomogeneities for both small and large detected lung nodules, in addition to the integration with the extracted geometric features. Finally, a deep autoencoder (AE) classifier is fed by the above two feature groups to distinguish between the malignant and benign nodules. To evaluate the proposed framework, we used the publicly available data from the Lung Image Database Consortium (LIDC). We used a total of 727 nodules that were collected from 467 patients. The proposed system demonstrates the promise to be a valuable tool for the detection of lung cancer evidenced by achieving a nodule classification accuracy of 92.20%

A generalized deep learning-based diagnostic system for early diagnosis of various types of pulmonary nodules

© The Author(s) 2018. A novel framework for the classification of lung nodules using computed tomography scans is proposed in this article. To get an accurate diagnosis of the detected lung nodules, the proposed framework integrates the following 2 groups of features: (1) appearance features modeled using the higher order Markov Gibbs random field model that has the ability to describe the spatial inhomogeneities inside the lung nodule and (2) geometric features that describe the shape geometry of the lung nodules. The novelty of this article is to accurately model the appearance of the detected lung nodules using a new developed seventh-order Markov Gibbs random field model that has the ability to model the existing spatial inhomogeneities for both small and large detected lung nodules, in addition to the integration with the extracted geometric features. Finally, a deep autoencoder classifier is fed by the above 2 feature groups to distinguish between the malignant and benign nodules. To evaluate the proposed framework, we used the publicly available data from the Lung Image Database Consortium. We used a total of 727 nodules that were collected from 467 patients. The proposed system demonstrates the promise to be a valuable tool for the detection of lung cancer evidenced by achieving a nodule classification accuracy of 91.20%

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Receiver development for BICEP Array, a next-generation CMB polarimeter at the South Pole

A detection of curl-type (B-mode) polarization of the primary CMB would be direct evidence for the inflationary paradigm of the origin of the Universe. The Bicep/Keck Array (BK) program targets the degree angular scales, where the power from primordial B-mode polarization is expected to peak, with ever-increasing sensitivity and has published the most stringent constraints on inflation to date. Bicep Array (BA) is the Stage-3 instrument of the BK program and will comprise four Bicep3-class receivers observing at 30/40, 95, 150 and 220/270 GHz with a combined 32,000+ detectors; such wide frequency coverage is necessary for control of the Galactic foregrounds, which also produce degree-scale B-mode signal. The 30/40 GHz receiver is designed to constrain the synchrotron foreground and has begun observing at the South Pole in early 2020. By the end of a 3-year observing campaign, the full Bicep Array instrument is projected to reach σr between 0.002 and 0.004, depending on foreground complexity and degree of removal of B-modes due to gravitational lensing (delensing). This paper presents an overview of the design, measured on-sky performance and calibration of the first BA receiver. We also give a preview of the added complexity in the time-domain multiplexed readout of the 7,776-detector 150 GHz receiver

An Estimate of the Incidence of Prostate Cancer in Africa: A Systematic Review and Meta-Analysis

Prostate cancer (PCa) is rated the second most common cancer and sixth leading cause of cancer deaths among men globally. Reports show that African men suffer disproportionately from PCa compared to men from other parts of the world. It is still quite difficult to accurately describe the burden of PCa in Africa due to poor cancer registration systems.We systematically reviewed the literature on prostate cancer in Africa and provided a continentwide incidence rate of PCa based on available data in the regio

Observing low elevation sky and the CMB Cold Spot with BICEP3 at the South Pole

BICEP3 is a 520 mm aperture on-axis refracting telescope at the South Pole, which observes the polarization of the cosmic microwave background (CMB) at 95 GHz to search for the B-mode signal from inflationary gravitational waves. In addition to this main target, we have developed a low-elevation observation strategy to extend coverage of the Southern sky at the South Pole, where BICEP3 can quickly achieve degree-scale E-mode measurements over a large area. An interesting E-mode measurement is probing a potential polarization anomaly around the CMB Cold Spot. During the austral summer seasons of 2018-19 and 2019-20, BICEP3 observed the sky with a flat mirror to redirect the beams to various low elevation ranges. The preliminary data analysis shows degree-scale E-modes measured with high signal-to-noise ratio

Analysis of Temperature-to-Polarization Leakage in BICEP3 and Keck CMB Data from 2016 to 2018

The Bicep/Keck Array experiment is a series of small-aperture refracting telescopes observing degree-scale Cosmic Microwave Background polarization from the South Pole in search of a primordial B-mode signature. As a pair differencing experiment, an important systematic that must be controlled is the differential beam response between the co-located, orthogonally polarized detectors. We use high-fidelity, in-situ measurements of the beam response to estimate the temperature-to-polarization (T → P) leakage in our latest data including observations from 2016 through 2018. This includes three years of Bicep3 observing at 95 GHz, and multifrequency data from Keck Array. Here we present band-averaged far-field beam maps, differential beam mismatch, and residual beam power (after filtering out the leading difference modes via deprojection) for these receivers. We show preliminary results of "beam map simulations," which use these beam maps to observe a simulated temperature (no Q/U) sky to estimate T → P leakage in our real data

Analysis of Temperature-to-Polarization Leakage in BICEP3 and Keck CMB Data from 2016 to 2018

The Bicep/Keck Array experiment is a series of small-aperture refracting telescopes observing degree-scale Cosmic Microwave Background polarization from the South Pole in search of a primordial B-mode signature. As a pair differencing experiment, an important systematic that must be controlled is the differential beam response between the co-located, orthogonally polarized detectors. We use high-fidelity, in-situ measurements of the beam response to estimate the temperature-to-polarization (T → P) leakage in our latest data including observations from 2016 through 2018. This includes three years of Bicep3 observing at 95 GHz, and multifrequency data from Keck Array. Here we present band-averaged far-field beam maps, differential beam mismatch, and residual beam power (after filtering out the leading difference modes via deprojection) for these receivers. We show preliminary results of "beam map simulations," which use these beam maps to observe a simulated temperature (no Q/U) sky to estimate T → P leakage in our real data