Multidisciplinary approach to the prenatal diagnosis and post natal management of a large suprasellar arachnoid cyst: A case report

Arachnoid cysts are intra-arachnoid sacs filled with cerebrospinal fluid representing a rare occurence in neonates. We report the case of a suprasellar arachnoid cyst diagnosed prenatally at 21 weeks gestation on routine obstetric ultrasound. A cystic lesion was picked up incidentally at routine antenatal scan. The cyst was noted to be increasing in size over a series of radiological scans. The cyst was diagnosed as a suprasellar arachnoid cyst compressing the third ventricle and bilateral lateral ventricles. A left pteryonal craniotomy for cystocisternostomy of large suprasellar cyst was performed initially. Within a month the cyst recurred with clinical and radiological evidence. An Endoscopic Third Ventriculostomy (ETV) with fenestration was performed.The patient was shifted to the NICU and discharged after 3 days in a stable condition. Patient was followed after 1 week and reassured and advised for one year follow-up

Rational Cubic Spline Interpolation for Monotonic Interpolating Curve with C 2

Monotonicity preserving interpolation is very important in many sciences and engineering based problems. This paper discuss the monotonicity preserving interpolation for monotone data set by using C2 rational cubic spline interpolant (cubic/quadratic) with three parameters. The data dependent sufficient conditions for the monotonicity are derived with two degree freedom. Numerical results suggests that the proposed C2 rational cubic spline preserves the monotonicity of the data and outperform the performance of the other rational cubic spline schemes in term of visually pleasing

Smart Mobility Cities: Connecting Bristol and Kuala Lumpur project report

Financed by the British Council Institutional Links program this Smart Mobility Cities project has opened a fascinating window on a journey of discovery linking Bristol and Kuala Lumpur. This journey was in part directed towards the realisation of Smart Mobility solutions to the socio-economic and environmental challenges of global urbanisation. Beyond this, the journey was also concerned to strengthen research and innovation partnerships between the UK and the emerging knowledge economy of Malaysia, enabling UK social scientists to collaborate on challenging global issues with international researchers and vice versa. This Smart Mobility Cities project report presents innovative, creative and yet fully practical solutions for these societal challenges. Solutions that explore a range of opportunities, whichinclude those arising from new urban governance requirements, and which are in-line with visions for sustainable urban mobility.These Smart Mobility solutions have arisen from intensive co-design and co-creation engagement with a diversity of stakeholders. Research co-production has linked the principal university partners of the University of the West of England (UWE), Bristol, and Taylor’sUniversity, Kuala Lumpur, together with the Malaysia Institute of Transport (MITRANS), Universiti Teknologi Mara, and the University Sains Malaysia (USM) in intensive engagement with stakeholder interests in both UK and Malaysia over a two-year period

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

CREATIVITY IS EVERYONE’S BUSINESS: HOW TO ENHANCE EMPLOYEE CREATIVITY IN TELECOMMUNICATION SECTOR

With rapid cultural, demographical and economic changes in knowledge oriented economy, employee creativity has become a challenge for organizations, as this works as a core competence. We suggest that leaders with ethical commitment help to nourish creativity in employees. Using social learning theory, authors examined the influence of ethical leadership on employee creativity through the mediation of self-efficacy. This study also explored the moderating role of uncertainty avoidance between the relationship of ethical leadership and employee creativity. Data was collected from 180 employees along with their supervisors from four different telecommunication companies working in Pakistan. The questionnaire was adopted and tested on the criteria of five point Likert scale. Regression and Correlation tests were used to check hypothesis. Supervisors of these four companies evaluated the creativity of the selected staff member groups while the employees and staff members reported the perceptions about their supervisors in terms of ethical leadership. Results showed that ethical leadership was positively related to employee creativity and this relationship was mediated by self-efficacy and this mediation was partial. There was significant negative relationship between uncertainty avoidance and employee creativity, this is the main aspect of present study. According to the results uncertainty is negatively associated with the employee creativity it means high uncertainty results in low creativity of employees. This study was conducted in Pakistani context where uncertain attitude is very common in society so uncertainty avoidance affects creativity of the employee in Pakistani organizations. Our study offer practical implications for telecommunication companies in order to achieve competitive advantage by enhancing employee creativity, as employee creativity makes organization creative

Image Interpolation Using a Rational Bi-Cubic Ball

This study deals with the application of new rational bi-cubic Ball function with six parameters in image interpolation, especially for the grayscale image. These six free parameters can be modified to get better and quality image resolution, and refine the shape of the interpolating surface. This bivariate rational Ball function has been extended from univariate cases by using a tensor product approach. The proposed scheme is tested for image upscaling with factors of two and four through an efficient algorithm. The effectiveness of the proposed scheme is measured by using an image quality assessment (IQA), such as peak-signal-to-noise-ratio (PSNR), root mean square error (RMSE) or feature similarity (FSIM) index. Numerical and graphical results with comparisons against some existing scheme are presented by using MATLAB. The proposed scheme resulted in higher PSNR and FSIM, and smaller RMSE. Thus, the new rational bi-cubic Ball with six parameters is better than the existing scheme via an efficient algorithm

An IoT and machine learning solutions for monitoring agricultural water quality: a robust framework

All living things, comprising animals, plants, and people require water to survive. The world is covered in water, just 1 percent of it is fresh and functional. The importance and value of freshwater have increased due to population growth and rising water demands. Approximately more than 70 percent of the world's freshwater is used for agriculture. Agricultural employees are the least productive, inefficient, and heavily subsidized water users in the world. They also utilize the most water overall. Irrigation consumes a considerable amount of water. The field's water supply needs to be safeguarded. A critical stage in estimating agricultural production is crop irrigation. The global shortage of fresh water is a serious issue, and it will only get worse in the years to come. Precision agriculture and intelligent irrigation are the only solutions that will solve the aforementioned issues. Smart irrigation systems and other modern technologies must be used to improve the quantity of high-quality water used for agricultural irrigation. Such a system has the potential to be quite accurate, but it requires data about the climate and water quality of the region where it will be used. This study examines the smart irrigation system using the Internet of Things (IoT) and cloud-based architecture. The water's temperature, pH, total dissolved solids (TDS), and turbidity are all measured by this device before the data is processed in a cloud using the range of machine learning (ML) approaches. Regarding water content limits, farmers are given accurate information. Farmers can increase production and water quality by using effective irrigation techniques. ML methods comprising support vector machines (SVM), random forests (RF), linear regression, Naive Bayes, and decision trees (DT) are used to categorize pre-processed data sets. Performance metrics like accuracy, precision, recall, and f1-score are used to calculate the performance of ML algorithms