Titania photocatalysts have great potential as remidiators of air pollution. While various aspects of photocatalyst synthesis, adsorption and photoactivity have been investigated, thorough understanding of the particle surface behavior has...

PurposeWorking women being housewives have to face major problems. They have to trade off between work domain and family life domain, in perspective sector and area chosen. This study investigates the factors behind work‐life conflict experienced by women with responsibilities and type of work arrangement experiencedDesign/methodology/approachThe study is conducted by exploring the responses of 100 women working in 25 different banks (public as well as private banks) in non‐contrived environment using random sampling in Attock and Islamabad cities of Pakistan. Regression and correlation is used for statistical analysisFindingsThe impact of women's earning potentials, household responsibilities, workplace environment and financial needs is analyzed on women work‐life conflict. Results from the study indicate that household responsibilities and workplace environment are strongly correlated to women work‐life conflict. Response rate is 75 percent and all the values for Cronbach Alpha are agreeable. Women earning potential and workplace environment are negatively related while household responsibilities and financial needs are positively correlated to women work‐life conflictResearch limitations/implicationsThis research selected sample from only two cities Pakistan i.e. Attock and Islamabad. Future studies could select other cities and compare results with city of selected sample. This research used random sampling procedure, which is the main limitation of this study. Future studies could use stratified random sampling procedure with more sample size.Practical implicationsIt is hoped that the findings of this study will assist the human resource managers, practitioners and strategy makers to better understand women problems.Originality/valueThe added value of this paper is to link theory and practice, and explore the working women life conflict with job environment. Few studies have conducted over the years under this perspective in the Pakistan.

Chronic obstructive pulmonary disease (COPD) is a lung disease that is not fully reversible and one of the leading causes of morbidity and mortality in the world. Early detection and diagnosis of COPD can increase the survival rate and reduce the risk of COPD progression in patients. Currently, the primary examination tool to diagnose COPD is spirometry. However, computed tomography (CT) is used for detecting symptoms and sub-type classification of COPD. Using different imaging modalities is a difficult and tedious task even for physicians and is subjective to inter-and intra-observer variations. Hence, developing methods that can automatically classify COPD versus healthy patients is of great interest. In this paper, we propose a 3D deep learning approach to classify COPD and emphysema using volume-wise annotations only. We also demonstrate the impact of transfer learning on the classification of emphysema using knowledge transfer from a pre-trained COPD classification model.

This paper focuses on designing a search algorithm that the DustySWARM team used in the 2019 NASA Swarmathon competition. The developed search algorithm will be implemented and tested on multiple rovers, a.k.a. Swarmies or Swarm Robots. Swarmies are compact rovers, designed by NASA to mimic Ants behavior and perform an autonomous search for simulated Mars resources. This effort aimed to assist NASA's mission to explore the space and discover new resources on the Moon and Mars. NASA's going-on project has the goal to send robots that explore and collect resources for analysis before sending Astronauts, as the swarm option is safer and more affordable. All rovers must utilize the exact algorithm and collaborate and cooperate to find all available resources in their search path and retrieve them to the space station location. Additionally, swarmies will autonomously search while avoiding obstacles and mapping the surrounding environment for future missions. This algorithm allows a swarm of six robots to search an unknown area for simulated resources called AprilTags (cubes with QR codes). The code was developed using C/C++, GitHub, and Robotics Operation Systems (ROS) and tested by utilizing the Gazebo Simulation environment and by running physical trials on the swarmies. The team analyzed a few algorithms from previous years and other researchers then developed the Radiating L-Shape Search (RLS) Algorithm. This paper will summarize the algorithm design, code development, and trial results that were provided to the NASA Space Exploration Engineering team.

Acute mesenteric ischemia (AMI) is a rare surgical emergency as it involves perfusion and need frequent surgical interventions. It is a life threatening emergency with a poor prognosis. It is classified according to the etiological basis thromboembolism, non-obstructive and venous origin. AMI has various risk factors ranging from cardiac arrhythmias to the intraabdominal hypertension. Apart from the signs and symptoms, the multi-detector computer tomography remains a diagnostic tool with accuracy. In the management of AMI patients' initial resuscitation, hydration and analgesia play important role, however the operative /interventional management is either endovascular thrombectomy with or without stenting when there is no bowel involvement or peritonitis. The laparotomy with open vascular thrombectomy with vascular graft, it is indicated when bowel involvement and peritonitis patients. Often the whole bowel is gangrenous and no further treatment is needed because of certain mortality. The 2 nd step is to know the extent of bowel involvement meticulously and resection of bowel with necrosis or gangrene with anastomosis, further relook laparotomies and resection of the bowel may be need. Initially abdomen will be closed with Bagota bag or VAC (Vacuum Assisted Closed) dressing and final staged abdominal closer, once pathology resolves completely. As far as prevention of all types