An Efficient Ensemble Method Using K-Fold Cross Validation for the Early Detection of Benign and Malignant Breast Cancer

In comparison to all other malignancies, breast cancer is the most common form of cancer, among women. Breast cancer prediction has been studied by several researchers and is considered a serious threat to women. Clinicians are finding it difficult to create a treatment approach that will help patients live longer, due to the lack of solid predictive models. Rates of this malignancy have been observed to rise, more with industrialization and urbanization, as well as with early detection facilities. It is still considerably more prevalent in very developed countries, but it is rapidly spreading to developing countries as well. The purpose of this work is to offer a report on the disease of breast cancer in which we used available technical breakthroughs to construct breast cancer survivability prediction models. The Machine Learning (ML) techniques, namely Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree (DT) Classifier, Random Forests (RF), and Logistic Regression (LR) is used as base Learners and their performance has been compared with the ensemble method, eXtreme Gradient Boosting (XGBoost).  For performance comparison, we employed the k-fold cross-validation method to measure the unbiased estimate of these prediction models. The results indicated that XGBoost outperformed with an accuracy of 97.81% compared to other ML algorithms

An Efficient Ensemble Method Using K-Fold Cross Validation for the Early Detection of Benign and Malignant Breast Cancer

In comparison to all other malignancies, breast cancer is the most common form of cancer, among women. Breast cancer prediction has been studied by several researchers and is considered a serious threat to women. Clinicians are finding it difficult to create a treatment approach that will help patients live longer, due to the lack of solid predictive models. Rates of this malignancy have been observed to rise, more with industrialization and urbanization, as well as with early detection facilities. It is still considerably more prevalent in very developed countries, but it is rapidly spreading to developing countries as well. The purpose of this work is to offer a report on the disease of breast cancer in which we used available technical breakthroughs to construct breast cancer survivability prediction models. The Machine Learning (ML) techniques, namely Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree (DT) Classifier, Random Forests (RF), and Logistic Regression (LR) is used as base Learners and their performance has been compared with the ensemble method, eXtreme Gradient Boosting (XGBoost).  For performance comparison, we employed the k-fold cross-validation method to measure the unbiased estimate of these prediction models. The results indicated that XGBoost outperformed with an accuracy of 97.81% compared to other ML algorithms

Effects of ultrasound on the performance improvement of wastewater microfiltration through a porous ceramic filter

Filtration under an ultrasonic field is a technique that is gaining importance in the wastewater treatment research field, not only due to its ability as a cleaning mechanism, but also as a filtration intensifier. The main objective of this research was the study of the influence of ultrasonic waves on the filtration of theoilfield wastewater (known as produced water) in order to increase the operation performance and filter medium regenerative effectiveness. A 0.016 m2 hollow cylindrical porous ceramic filter was submitted to the filtration of produced water by two mechanisms: conventional filtration under vacuum and filtration under theinfluence of ultrasonic waves. Experiments were carried out using synthetic produced water by analyzing the variables oil and grease content (O&G) and total suspended solids (TSS) for each filtration run. Backwashing of the filter medium with distilled water was also performed to evaluate the regeneration efficiency. During conventional filtration, permeate flux decreased gradually, becoming stable around 0.06 cm3.cm-2.s-1. Furthermore, in the filtration assisted by ultrasound, the permeate flux was around 0.15 cm3.cm-2.s-1. Therefore, ultrasonic waves provided an increase of about 150% in the permeate flux. Moreover, the sonication improved filter medium regeneration effectiveness, even under conditions of high TSS and O&G contents. Taking into consideration the very positive results associated with the application of ultrasonicwaves, this filtration technique is likely to become an important industrial process

Glamdring: automatic application partitioning for Intel SGX

Trusted execution support in modern CPUs, as offered by Intel SGX enclaves , can protect applications in untrusted environments. While prior work has shown that legacy applications can run in their entirety inside enclaves, this results in a large trusted computing base (TCB). Instead, we explore an approach in which we partition an applica- tion and use an enclave to protect only security-sensitive data and functions, thus obtaining a smaller TCB. We describe Glamdring , the first source-level parti- tioning framework that secures applications written in C using Intel SGX. A developer first annotates security- sensitive application data. Glamdring then automatically partitions the application into untrusted and enclave parts: (i) to preserve data confidentiality, Glamdring uses dataflow analysis to identify functions that may be ex- posed to sensitive data; (ii) for data integrity, it uses back- ward slicing to identify functions that may affect sensitive data. Glamdring then places security-sensitive functions inside the enclave, and adds runtime checks and crypto- graphic operations at the enclave boundary to protect it from attack. Our evaluation of Glamdring with the Mem- cached store, the LibreSSL library, and the Digital Bitbox bitcoin wallet shows that it achieves small TCB sizes and has acceptable performance overheads

Extraction process optimization of flavonoid and in vitro amylase inhibitory effect of purified quercetin derivative from Amorphophallus paeoniifolius tubers

544-556Amorphophallus paeoniifolius (Elephant foot yam) is a prominent tuberous plant utilized across several parts of India to treat various ailments such as a tumour, haemorrhage, microbial infections, cough, bronchitis, diabetes, anaemia, and hepato-gastro and cardiovascular diseases. In this context, the present study aims to optimize the extraction process of the flavonoid and to study the in vitro amylase inhibitory effect of purified flavonoid moiety. The Shake flask method with different extraction solvents was adopted to quantify the flavonoid content. Central composite design (CCD) based response surface methodology (RSM) was formulated to optimize the extraction process. Three-dimensional preparative chromatography (3D PTLC) was executed to purify the flavonoid content and high-resolution liquid chromatography-mass spectrometry (HRLC-MS) was adopted to predict the structure. 3,5-dinitrosalicylic acid (DNS) based spectrophotometry method was used to determine the amylase inhibitory property. All the analyses were subjected to standard statistical tests. The developed model for the extraction optimization process was found to be near significant (P = 0.242) with temperature as a significant variable (P = 0.029), and a 107-fold increase (71.11±0.5 mg/g tissue) of flavonoid content was recorded. A strong yellow colour spot (flavonoid fraction) was eluted using 3D PTLC technique and the molecule was identified as quercetin derivative (m/z 447) by the direct MS method. Significant amylase inhibition (36.1±2.1%) recorded by purified quercetin derivative has documented the utilization of A. paeoniifolius tubers as classical traditional medicine

Bio-processing of algal bio-refinery: a review on current advances and future perspectives

Microalgae biomass contains various useful bio-active components. Microalgae derived biodiesel has been researched for almost two decades. However, sole biodiesel extraction from microalgae is time-consuming and is not economically feasible due to competitive fossil fuel prices. Microalgae also contains proteins and carbohydrates in abundance. Microalgae are likewise utilized to extract high-value products such as pigments, anti-oxidants and long-chain polyunsaturated fatty acids which are useful in cosmetic, pharmaceutical and nutraceutical industry. These compounds can be extracted simultaneously or sequentially after biodiesel extraction to reduce the total expenditure involved in the process. This approach of bio-refinery is necessary to promote microalgae in the commercial market. Researchers have been keen on utilizing the bio-refinery approach to exploit the valuable components encased by microalgae. Apart from all the beneficial components housed by microalgae, they also help in reducing the anthropogenic CO2 levels of the atmosphere while utilizing saline or wastewater. These benefits enable microalgae as a potential source for bio-refinery approach. Although life-cycle analysis and economic assessment do not favor the use of microalgae biomass feedstock to produce biofuel and co-products with the existing techniques, this review still aims to highlight the beneficial components of microalgae and their importance to humans. In addition, this article also focuses on current and future aspects of improving the feasibility of bio-processing for microalgae bio-refinery

Financial feasibility of end-user designed rainwater harvesting and greywater reuse systems for high water use households

© 2017, The Author(s). Water availability pressures, competing end-uses and sewers at capacity are all drivers for change in urban water management. Rainwater harvesting (RWH) and greywater reuse (GWR) systems constitute alternatives to reduce drinking water usage and in the case of RWH, reduce roof runoff entering sewers. Despite the increasing popularity of installations in commercial buildings, RWH and GWR technologies at a household scale have proved less popular, across a range of global contexts. For systems designed from the top-down, this is often due to the lack of a favourable cost-benefit (where subsidies are unavailable), though few studies have focused on performing full capital and operational financial assessments, particularly in high water consumption households. Using a bottom-up design approach, based on a questionnaire survey with 35 households in a residential complex in Bucaramanga, Colombia, this article considers the initial financial feasibility of three RWH and GWR system configurations proposed for high water using households (equivalent to >203L per capita per day). A full capital and operational financial assessment was performed at a more detailed level for the most viable design using historic rainfall data. For the selected configuration (‘Alt 2’), the estimated potable water saving was 44% (equivalent to 131m3/year) with a rate of return on investment of 6.5% and an estimated payback period of 23years. As an initial end-user-driven design exercise, these results are promising and constitute a starting point for facilitating such approaches to urban water management at the household scale

Recent advances in organic synthesis using light-mediated n-heterocyclic carbene catalysis

The combination of photocatalysis with other ground state catalytic systems have attracted much attention recently due to the enormous synthetic potential offered by a dual activation mode. The use of N-heterocyclic carbene (NHC) as organocatalysts emerged as an important synthetic tool. Its ability to harness umpolung reactivity by the formation of the Breslow intermediate has been employed in the synthesis of thousands of biologically important compounds. However, the available coupling partners are relatively restricted, and its combination with other catalytic systems might improve its synthetic versatility. Thus, merging photoredox and N-heterocyclic carbene (NHC) catalysis has emerged recently as a powerful strategy to develop new transformations and give access to a whole new branch of synthetic possibilities. This review compiles the NHC catalyzed methods mediated by light, either in the presence or absence of an external photocatalyst, that have been described so far, and aims to give an accurate overview of the potential of this activation modeL.M. acknowledges the Autonomous Community of Madrid (CAM) for the financial support (PEJD-2019-PRE/AMB-16640 and SI1/PJI/ 2019-00237) and for an “Atracción de Talento Investigador” contract (2017-T2/AMB-5037

2017 update of the WSES guidelines for emergency repair of complicated abdominal wall hernias

Emergency repair of complicated abdominal wall hernias may be associated with worsen outcome and a significant rate of postoperative complications. There is no consensus on management of complicated abdominal hernias. The main matter of debate is about the use of mesh in case of intestinal resection and the type of mesh to be used. Wound infection is the most common complication encountered and represents an immense burden especially in the presence of a mesh. The recurrence rate is an important topic that influences the final outcome. A World Society of Emergency Surgery (WSES) Consensus Conference was held in Bergamo in July 2013 with the aim to define recommendations for emergency repair of abdominal wall hernias in adults. This document represents the executive summary of the consensus conference approved by a WSES expert panel. In 2016, the guidelines have been revised and updated according to the most recent available literature.Peer reviewe

Foam-Mat Freeze-Drying of Blueberry Juice by Using Trehalose-β-Lactoglobulin and Trehalose-Bovine Serum Albumin as Matrices

This study aimed to evaluate the effect of pure protein compounds and trehalose incorporated into blueberry juice for foam-mat freeze-drying on the foam and powder properties. Foam-mat freeze-drying (FMFD) of blueberry juice was tested at − 55 °C for 24 h. Matrices used were trehalose + β-lactoglobulin (T3BL1) and trehalose + bovine serum albumin (T3A1) and compared with maltodextrin + whey protein isolate (M3W1). Physicochemical properties of foam and powder, e.g., foam stability, foam density, moisture, rehydration time, color, particle morphology, total phenolic, and anthocyanins (total and individuals), were investigated. T3BL1 and T3A1 had more stable foam than M3W1. However, overrun of T3BL1 and T3A1 foamed were inferior to the M3W1 sample. The M3W1 sample recovered 79% powder (dry weight) and was superior to others. Rehydration time of powdered T3BL1 and T3A1, with bulk densities of 0.55–0.60 g cm−3, was the fastest (34–36 s). The blueberry powders of M3W1 showed more irregular particle size and shape, while the samples with trehalose and pure proteins generated particles of more uniform size with obvious pores. T3BL1 and T3A1 showed less redness (a*) values than the M3W1 product. All samples were considered pure red due to hue values < 90. M3W1 was superior in total phenolic content (TPC) and total monomeric anthocyanins (TMA) compared with both samples made with trehalose + β-lactoglobulin and trehalose+bovine serum albumin. Delphinidin-3-glucoside (Del3Gl) concentration was found to be higher in M3W1. Also, M3W1 had higher cyanidin-3-glucoside (Cyn3Gl) and malvidin-3-glucoside (Mal3Gl) concentration. M3W1 also prevented the degradation of these bioactive compounds better than the other FMFD samples. The use of pure proteins and trehalose as matrices in the FMFD process had little advantage compared with maltodextrin/whey protein isolate. Thus, maltodextrin/whey protein isolate seems an ideal matrix for the manufacture of FMFD blueberry