Random Fixed Points For Occasionally Weakly Compatible Mappings

In this paper, we obtain common random fixed point theorems for two pairs of occasionally weakly compatible self random mappings under contractive conditions involving two generalized altering distance functions in a complete separable metric space. Keywords: Common random fixed point, Complete separable metric space, Generalized altering distance function, Occasionally weakly compatible mappings, Point of coincidence

CuisineNet: Food Attributes Classification using Multi-scale Convolution Network

Diversity of food and its attributes represents the culinary habits of peoples from different countries. Thus, this paper addresses the problem of identifying food culture of people around the world and its flavor by classifying two main food attributes, cuisine and flavor. A deep learning model based on multi-scale convotuional networks is proposed for extracting more accurate features from input images. The aggregation of multi-scale convolution layers with different kernel size is also used for weighting the features results from different scales. In addition, a joint loss function based on Negative Log Likelihood (NLL) is used to fit the model probability to multi labeled classes for multi-modal classification task. Furthermore, this work provides a new dataset for food attributes, so-called Yummly48K, extracted from the popular food website, Yummly. Our model is assessed on the constructed Yummly48K dataset. The experimental results show that our proposed method yields 65% and 62% average F1 score on validation and test set which outperforming the state-of-the-art models.Comment: 8 pages, Submitted in CCIA 201

THE INFLUENCE OF RESIN MODIFIERS ON THE PERFORMANCE OF HOT MIX ASPHALT

ABSTRACT In order to study the influence of resin modifiers materials on the performance of hot mix asphalts (HMA), two types of resin modifiers were selected. One was anUnsaturated Polyester Resin (UPR) and the other was an Epoxy Resin (ER). Also, unsaturated polyester resin mixed with 3% epoxy resin (UPRER) was used according to test results, which gave preference to 3% additions. Marshal test was conducted to study the stability, flow, bulk density, air voids (AV), voids in mineral aggregate (VMA) and voids filled with bitumen (VFA) for controlled hot asphalt mixtures and resin: modified mixtures at various resin modifiers contents. A computer program named BISAR was also used to determine the total stress, strain and displacement in x-y, and z-direction for flexible pavements constructed with these hot mix asphalts modified with resin additives.Experimental results showed that all resin-modified asphalt mixtures have higher flow, bulk density and VFA compared with control mixture. The stability of asphalt mixtures with UPPER was always higher than the control mixture. Unlike, for type ER and UPR the stability was lower than the control mixture up to 1% and 2% respectively then they increase. The UPRER gave higher stability, flow, AV and VMA than the other types. Moreover, the UPR gave the highest value of bulk density and VFA. The maximum stability occurs at 3% resin modifiers content for all types. The total stress and strain relatively increase with the increase of mix depth till 10 cm, then they decrease for all types of resin modifiers. The maximum total stresses and strain in case of UPRER are higher values than those achieved by ER and UPR respectively. The total displacement in case of UPRER is higher than that achieved by ER and UPR respectively. As resin modifiers can improve the field performance of asphalt mixes comprehensively, they will be of great benefit to the engineering field

Retinal Optic Disc Segmentation using Conditional Generative Adversarial Network

This paper proposed a retinal image segmentation method based on conditional Generative Adversarial Network (cGAN) to segment optic disc. The proposed model consists of two successive networks: generator and discriminator. The generator learns to map information from the observing input (i.e., retinal fundus color image), to the output (i.e., binary mask). Then, the discriminator learns as a loss function to train this mapping by comparing the ground-truth and the predicted output with observing the input image as a condition.Experiments were performed on two publicly available dataset; DRISHTI GS1 and RIM-ONE. The proposed model outperformed state-of-the-art-methods by achieving around 0.96% and 0.98% of Jaccard and Dice coefficients, respectively. Moreover, an image segmentation is performed in less than a second on recent GPU.Comment: 8 pages, Submitted to 21st International Conference of the Catalan Association for Artificial Intelligence (CCIA 2018

Knowledge of dental academics about the COVID-19 pandemic: a multi-country online survey

Background: COVID-19 is a global pandemic affecting all aspects of life in all countries. We assessed COVID-19 knowledge and associated factors among dental academics in 26 countries. Methods: We invited dental academics to participate in a cross-sectional, multi-country, online survey from March to April 2020. The survey collected data on knowledge of COVID-19 regarding the mode of transmission, symptoms, diagnosis, treatment, protection, and dental treatment precautions as well as participants’ background variables. Multilevel linear models were used to assess the association between dental academics’ knowledge of COVID-19 and individual level (personal and professional) and country-level (number of COVID-19 cases/ million population) factors accounting for random variation among countries. Results: Two thousand forty-five academics participated in the survey (response rate 14.3%, with 54.7% female and 67% younger than 46 years of age). The mean (SD) knowledge percent score was 73.2 (11.2) %, and the score of knowledge of symptoms was significantly lower than the score of knowledge of diagnostic methods (53.1 and 85.4%, P < 0.0001). Knowledge score was significantly higher among those living with a partner/spouse than among those living alone (regression coefficient (B) = 0.48); higher among those with PhD degrees than among those with Bachelor of Dental Science degrees (B = 0.48); higher among those seeing 21 to 30 patients daily than among those seeing no patients (B = 0.65); and higher among those from countries with a higher number of COVID-19 cases/million population (B = 0.0007). Conclusions: Dental academics had poorer knowledge of COVID-19 symptoms than of COVID-19 diagnostic methods. Living arrangements, academic degrees, patient load, and magnitude of the epidemic in the country were associated with COVD-19 knowledge among dental academics. Training of dental academics on COVID-19 can be designed using these findings to recruit those with the greatest need

Knowledge of dental academics about the COVID-19 pandemic: a multi-country online survey.

BACKGROUND: COVID-19 is a global pandemic affecting all aspects of life in all countries. We assessed COVID-19 knowledge and associated factors among dental academics in 26 countries. METHODS: We invited dental academics to participate in a cross-sectional, multi-country, online survey from March to April 2020. The survey collected data on knowledge of COVID-19 regarding the mode of transmission, symptoms, diagnosis, treatment, protection, and dental treatment precautions as well as participants' background variables. Multilevel linear models were used to assess the association between dental academics' knowledge of COVID-19 and individual level (personal and professional) and country-level (number of COVID-19 cases/ million population) factors accounting for random variation among countries. RESULTS: Two thousand forty-five academics participated in the survey (response rate 14.3%, with 54.7% female and 67% younger than 46 years of age). The mean (SD) knowledge percent score was 73.2 (11.2) %, and the score of knowledge of symptoms was significantly lower than the score of knowledge of diagnostic methods (53.1 and 85.4%, P <  0.0001). Knowledge score was significantly higher among those living with a partner/spouse than among those living alone (regression coefficient (B) = 0.48); higher among those with PhD degrees than among those with Bachelor of Dental Science degrees (B = 0.48); higher among those seeing 21 to 30 patients daily than among those seeing no patients (B = 0.65); and higher among those from countries with a higher number of COVID-19 cases/million population (B = 0.0007). CONCLUSIONS: Dental academics had poorer knowledge of COVID-19 symptoms than of COVID-19 diagnostic methods. Living arrangements, academic degrees, patient load, and magnitude of the epidemic in the country were associated with COVD-19 knowledge among dental academics. Training of dental academics on COVID-19 can be designed using these findings to recruit those with the greatest need

Perceived preparedness of dental academic institutions to cope with the COVID-19 pandemic: a multi-country survey

Dental academic institutions are affected by COVID-19. We assessed the perceived COVID19 preparedness of these institutions and the characteristics of institutions with greater perceived preparedness. An international cross-sectional survey of dental academics was conducted from March to August 2020 to assess academics’ and institutional attributes, perceived preparedness, and availability of infection prevention and control (IPC) equipment. Principal component analysis (PCA) identified perceived preparedness components. Multilevel linear regression analysis assessed the association between perceived preparedness and fixed effect factors (academics’ and institutions’ attributes) with countries as random effect variable. Of the 1820 dental academics from 28 countries, 78.4% worked in public institutions and 75.2% reported temporary closure. PCA showed five components: clinic apparel, measures before and after patient care, institutional policies, and availability of IPC equipment. Significantly less perceived preparedness was reported in lower-middle income (LMICs) (B = −1.31, p = 0.006) and upper-middle income (UMICs) (B = −0.98, p = 0.02) countries than in high-income countries (HICs), in teaching only (B = −0.55, p &lt; 0.0001) and in research only (B = −1.22, p = 0.003) than teaching and research institutions and in institutions receiving ≤100 patients daily than those receiving &gt;100 patients (B = −0.38, p &lt; 0.0001). More perceived preparedness was reported by academics with administrative roles (B = 0.59, p &lt; 0.0001). Academics from low-income countries (LICs) and LMICs reported less availability of clinic apparel, IPC equipment, measures before patient care, and institutional policies but more measures during patient care. There was greater perceived preparedness in HICs and institutions with greater involvement in teaching, research, and patient care

The oncogene AAMDC links PI3K-AKT-mTOR signaling with metabolic reprograming in estrogen receptor-positive breast cancer

Adipogenesis associated Mth938 domain containing (AAMDC) represents an uncharacterized oncogene amplified in aggressive estrogen receptor-positive breast cancers. We uncover that AAMDC regulates the expression of several metabolic enzymes involved in the one-carbon folate and methionine cycles, and lipid metabolism. We show that AAMDC controls PI3K-AKT-mTOR signaling, regulating the translation of ATF4 and MYC and modulating the transcriptional activity of AAMDC-dependent promoters. High AAMDC expression is associated with sensitization to dactolisib and everolimus, and these PI3K-mTOR inhibitors exhibit synergistic interactions with anti-estrogens in IntClust2 models. Ectopic AAMDC expression is sufficient to activate AKT signaling, resulting in estrogen-independent tumor growth. Thus, AAMDC-overexpressing tumors may be sensitive to PI3K-mTORC1 blockers in combination with anti-estrogens. Lastly, we provide evidence that AAMDC can interact with the RabGTPase-activating protein RabGAP1L, and that AAMDC, RabGAP1L, and Rab7a colocalize in endolysosomes. The discovery of the RabGAP1L-AAMDC assembly platform provides insights for the design of selective blockers to target malignancies having the AAMDC amplification

Endomyocardial Fibrosis: Still a Mystery after 60 Years

The pathologist Jack N. P. Davies identified endomyocardial fibrosis in Uganda in 1947. Since that time, reports of this restrictive cardiomyopathy have come from other parts of tropical Africa, South Asia, and South America. In Kampala, the disease accounts for 20% of heart disease patients referred for echocardiography. We conducted a systematic review of research on the epidemiology and etiology of endomyocardial fibrosis. We relied primarily on articles in the MEDLINE database with either “endomyocardial fibrosis” or “endomyocardial sclerosis” in the title. The volume of publications on endomyocardial fibrosis has declined since the 1980s. Despite several hypotheses regarding cause, no account of the etiology of this disease has yet fully explained its unique geographical distribution

Laparoscopy in management of appendicitis in high-, middle-, and low-income countries: a multicenter, prospective, cohort study.

BACKGROUND: Appendicitis is the most common abdominal surgical emergency worldwide. Differences between high- and low-income settings in the availability of laparoscopic appendectomy, alternative management choices, and outcomes are poorly described. The aim was to identify variation in surgical management and outcomes of appendicitis within low-, middle-, and high-Human Development Index (HDI) countries worldwide. METHODS: This is a multicenter, international prospective cohort study. Consecutive sampling of patients undergoing emergency appendectomy over 6 months was conducted. Follow-up lasted 30 days. RESULTS: 4546 patients from 52 countries underwent appendectomy (2499 high-, 1540 middle-, and 507 low-HDI groups). Surgical site infection (SSI) rates were higher in low-HDI (OR 2.57, 95% CI 1.33-4.99, p = 0.005) but not middle-HDI countries (OR 1.38, 95% CI 0.76-2.52, p = 0.291), compared with high-HDI countries after adjustment. A laparoscopic approach was common in high-HDI countries (1693/2499, 67.7%), but infrequent in low-HDI (41/507, 8.1%) and middle-HDI (132/1540, 8.6%) groups. After accounting for case-mix, laparoscopy was still associated with fewer overall complications (OR 0.55, 95% CI 0.42-0.71, p < 0.001) and SSIs (OR 0.22, 95% CI 0.14-0.33, p < 0.001). In propensity-score matched groups within low-/middle-HDI countries, laparoscopy was still associated with fewer overall complications (OR 0.23 95% CI 0.11-0.44) and SSI (OR 0.21 95% CI 0.09-0.45). CONCLUSION: A laparoscopic approach is associated with better outcomes and availability appears to differ by country HDI. Despite the profound clinical, operational, and financial barriers to its widespread introduction, laparoscopy could significantly improve outcomes for patients in low-resource environments. TRIAL REGISTRATION: NCT02179112