A Safe Quick Technique for Placement of the First Access Port for Creation of Pneumoperitoneum

The authors recommend a modified open technique in placing the first port when intraabdominal adhesions are expected

Women entrepreneurial leaders as harbingers of economic growth: Evidences from an emerging market of South Asia

Claire Seaman - ORCID: 0000-0003-4818-5051 https://orcid.org/0000-0003-4818-5051Global economy is driven by entrepreneurs operating micro, small, medium, and large-scale enterprises (M-SMLEs). This probe integrates three distinct domains, entrepreneurship, leadership, and gender, particularly women. In a previous study, one of the co-authors investigated such phenomenon that comprised motivations and pre-and-post venture challenges for women entrepreneurial leaders and devised a conceptual framework. This inquiry applies quantitative methods to empirically test and validate such framework, and contribute towards pertinent theoretical underpinning. It avails post-positivism philosophy, deductive approach, and survey method. Data was garnered from women entrepreneurial leaders of Pakistan – a growing emerging market of South Asia. The sample size includes 308 samples (comprising micro, small, and medium-scale enterprises (M-SMEs), 100+ participants from each category. The capabilities, circumstances, and behavior of M-SMEs differ than those of such leaders from large-scale enterprises; therefore, they were ignored purposefully. Structural Equation Modeling (SEM) technique was availed for data analysis. Canons of reliability, validity, and triangulation assisted toward robust results. The findings reveal that motivation to become entrepreneur and need of situation appeared the most significant predictors for starting and leading a venture by women. In challenges before the start of business (discouragement from family and gender stereotypes, financial challenges, lack of entrepreneurial knowledge, and lack of access to market and workplace [in a male-dominated society]) appeared significant predictors in order. And in challenges after the start of business (lack of market research, lack of finance and sustainability, harassment from men, and gender stereotypes from employees) respectively appeared significant predictors of women entrepreneurial leadership.https://doi.org/10.17993/3cemp.2021.100347.137-16910pubpub

Improving hate speech detection using machine and deep learning techniques: A preliminary study

The increasing use of social media and information sharing has given major benefits to humanity. However, this has also given rise to a variety of challenges including the spreading and sharing of hate speech messages. Thus, to solve this emerging issue in social media, recent studies employed a variety of feature engineering techniques and machine learning or deep learning algorithms to automatically detect the hate speech messages on different datasets. However, most of the studies classify the hate speech related message using existing feature engineering approaches and suffer from the low classification results. This is because, the existing feature engineering approaches suffer from the word order problem and word context problem. In this research, identifying hateful content from latest tweets of twitter and classify them into several categories is studied. The categories identified are; Ethnicity, Nationality, Religion, Gender, Sexual Orientation, Disability and Other. These categories are further classified to identify the targets of hate speech such as Black, White, Asian belongs to Ethnicity and Muslims, Jews, Christians can be classified from Religion Category. An evaluation will be performed among the hateful content identified using deep learning model LSTM and traditional machine learning models which includes Linear SVC, Logistic Regression, Random Forest and Multinomial Nai¨ve Bayes to measure their accuracy and precision and their comparison on the live extracted tweets from twitter which will be used as our test dataset

Effective Image Segmentation using Composite Energy Metric in Levelset Based Curve Evolution

Accurate segmentation of anatomical organs in medical images is a complex task due to wide interpatient variability and several acquisition dependent artefacts. Moreover, image noise, low contrast and intensity inhomogeneity in medical data further amplifies the challeng. In this work, we propose an effective yet simple algorithm based on composite energy metric for precise detection of object boundaries. A number of methods have been proposed in literature for image segmentation; however, these methods employ individual characteristics of image including gradient, regional intensity or texture map. Segmentation based on individual featres often fail for complex images, especially for medical imagery. Accordingly, we propose that the segmentation quality can be improved by integrating local and global image features in the curve evolution. This work employs the classic snake model aka active contour model; however, the curve evolution force has been updated. In contast to the conventional image-based regional intensity statistics, the proposed snake model evolves using composite image energy. Hence, the proposed method offers a greater resistance to the local optima problem as well as initialization perturbations. Experimental results for both synthetic and 2D (Two Dimensional) real clinal images are presented in this work to validate the performance of the proposed method. The performance of the proposed model is evaluated with respect to expert-based manual ground truth. Accordingly, the proposed model achieves higher accuracy in comparison to the state-of-the-art region based segmentation methods of Lankton and Yin as reported in results section

The prevalence of waterpipe tobacco smoking among the general and specific populations: a systematic review

Abstract Background The objective of this study was to systematically review the medical literature for the prevalence of waterpipe tobacco use among the general and specific populations. Methods We electronically searched MEDLINE, EMBASE, and the ISI the Web of Science. We selected studies using a two-stage duplicate and independent screening process. We included cohort studies and cross sectional studies assessing the prevalence of use of waterpipe in either the general population or a specific population of interest. Two reviewers used a standardized and pilot tested form to collect data from each eligible study using a duplicate and independent screening process. We stratified the data analysis by country and by age group. The study was not restricted to a specific context. Results Of a total of 38 studies, only 4 were national surveys; the rest assessed specific populations. The highest prevalence of current waterpipe smoking was among school students across countries: the United States, especially among Arab Americans (12%-15%) the Arabic Gulf region (9%-16%), Estonia (21%), and Lebanon (25%). Similarly, the prevalence of current waterpipe smoking among university students was high in the Arabic Gulf region (6%), the United Kingdom (8%), the United States (10%), Syria (15%), Lebanon (28%), and Pakistan (33%). The prevalence of current waterpipe smoking among adults was the following: Pakistan (6%), Arabic Gulf region (4%-12%), Australia (11% in Arab speaking adults), Syria (9%-12%), and Lebanon (15%). Group waterpipe smoking was high in Lebanon (5%), and Egypt (11%-15%). In Lebanon, 5%-6% pregnant women reported smoking waterpipe during pregnancy. The studies were all cross-sectional and varied by how they reported waterpipe smoking. Conclusion While very few national surveys have been conducted, the prevalence of waterpipe smoking appears to be alarmingly high among school students and university students in Middle Eastern countries and among groups of Middle Eastern descent in Western countries

Detection And Quantification of Lung Nodules Using 3D CT images

In computer vision image detection and quantification play an important role. Image Detection and quantification is the process of identifying nodule position and the amount of covered area. The dataset which we have used for this research contains 3D CT lung images. In our proposed work we have taken 3D images and those are high-resolution images. We have compared the accuracy of the existing mask and our segmented images. The segmentation method that we have applied to these images is Sparse Field Method localized region-based segmentation and for Nodule detection, I have used ray projection. The ray projection method is efficient for making the point more visible by its x, y, and z components. like a parametric equation where the line crossing through a targeted point by that nodule is more dominated. The Frangi filter was to give a geometric shape to the nodule and we got 90% accurate detection. The high mortality rate associated with lung cancer makes it imperative that it be detected at an early stage. The application of computerized image processing methods has the potential to improve both the efficiency and reliability of lung cancer screening. Computerized tomography (CT) pictures are frequently used in medical image processing because of their excellent resolution and low noise. Computer-aided detection systems, including preprocessing and segmentation methods, as well as data analysis approaches, have been investigated in this research for their potential use in the detection and diagnosis of lung cancer. The primary objective was to research cutting-edge methods for creating computational diagnostic tools to aid in the collection, processing, and interpretation of medical imaging data. Nonetheless, there are still areas that need more work, such as improving sensitivity, decreasing false positives, and optimizing the identification of each type of nodule, even those of varying size and form

Detection And Quantification of Lung Nodules Using 3D CT images

In computer vision image detection and quantification play an important role. Image Detection and quantification is the process of identifying nodule position and the amount of covered area. The dataset which we have used for this research contains 3D CT lung images. In our proposed work we have taken 3D images and those are high-resolution images. We have compared the accuracy of the existing mask and our segmented images. The segmentation method that we have applied to these images is Sparse Field Method localized region-based segmentation and for Nodule detection, I have used ray projection. The ray projection method is efficient for making the point more visible by its x, y, and z components. like a parametric equation where the line crossing through a targeted point by that nodule is more dominated. The Frangi filter was to give a geometric shape to the nodule and we got 90% accurate detection. The high mortality rate associated with lung cancer makes it imperative that it be detected at an early stage. The application of computerized image processing methods has the potential to improve both the efficiency and reliability of lung cancer screening. Computerized tomography (CT) pictures are frequently used in medical image processing because of their excellent resolution and low noise. Computer-aided detection systems, including preprocessing and segmentation methods, as well as data analysis approaches, have been investigated in this research for their potential use in the detection and diagnosis of lung cancer. The primary objective was to research cutting-edge methods for creating computational diagnostic tools to aid in the collection, processing, and interpretation of medical imaging data. Nonetheless, there are still areas that need more work, such as improving sensitivity, decreasing false positives, and optimizing the identification of each type of nodule, even those of varying size and form

Introducing Dual Suspension System in Road Vehicles

The main objective of suspension system is to reduce the motions of the vehicle body with respect to road disturbances. The conventional suspension systems in road vehicles use passive elements such as springs and dampers to suppress the vibrations induced by the irregularities in the road. But these conventional suspension systems can suppress vibrations to a certain limit. This paper presents a novel idea to improve the ride quality of roads vehicles without compromising vehicle?s stability. The paper proposes the use of primary and secondary suspension to suppress the vibrations more effectively

Actuation Characteristics of 0.15mm Diameter Flexinol® and Biometal ® Wire Actuators for Robotic Applications

In this paper the actuation properties of two NiTi (Nickel Titanium) SMA (Shape Memory Alloy) actuators available under the commercial names of Flexinol ® and Biometal ® are investigated and compared with each other. Both actuators have diameter of 0.15mm and transformation temperature of 70 o C. The diameter of 0.15mm is selected because of best combination of force and cooling time. An experimental test rig specially designed and developed by the first author was used to conduct tests on the actuators. Both actuators were tested by supplying actuation voltages of 5 and 5.5V. Actuators were thermomechanically loaded for 100 cycles and their strains were recorded. The results of the tests show that 5.5V actuation resulted in greater strain. It was found from the test results that Biometal ® actuators produced more strain as compared to Flexinol ® actuators for both the actuation voltages. However, the drift results showed that higher strains in Biometal ® are due the permanent deformation of the same. This shows that Flexinol ® actuators possess better actuation characteristics as compared to Biometal ® actuators

Axisymmetric Predictions of Fluid Flow inside a Rotating Cavity System

Accurate prediction of fluid flow in the rotating cavity system is of practical interest as it is most commonly used in the gas turbine engines and compressors. This paper presents the numerical predictions of a rotating cavity flow system for Reynolds numbers of the range 1x105 < Re? < 4x105 and two different mass flow rates Cw=1092 and 2184. A finite-difference technique is employed for a Steady-state solution in the axisymmetric cylindrical polar coordinate frame of reference. The two low Reynolds number turbulence models, the low Reynolds number k-? model and the low Reynolds number second moment closure have been used to compute the basic characteristics of the flow inside the rotating cavity flow system. Different flow regions have been identified by computing flow structures and dimensions of those regions have also been studied under different flow rates. A comparison of the computed variation of moment coefficient of both the turbulence models are presented for the above mentioned parameters and the parametric effects on the moment coefficients have been discusse