Recent Advancement of Colorectal Cancer and Their Herbal Essential Oil Treatment

Colorectal cancer is the second most deadly type of cancer (CRC). In the upcoming decades, death and incidence rates would surely increase globally. Despite being disproportionately high in high-income countries, CRC-related mortality is also on the rise in low- and middle-income countries. Early diagnosis of CRC allows for both surgical and medicinal treatment options. Due to the high likelihood of recurrence and the rising rate of treatment failure brought on by cancer medicine resistance, it is regrettable that there is a significant treatment failure rate. Due to early discovery and treatment of CRC, there is a chance of survival in wealthy nations. Contrarily, these resources are noticeably scarce in less developed countries. It is crucial to inform the public about CRC\u27s current situation, its cause, progression, risk factors, and therapy. As a result, we have included in this review all of the most recent data on the global epidemiology, drug resistance, challenges, risk factors, and preventative and therapeutic approaches for CRC. Guidelines for CRC prevention and therapy are briefly reviewed, as well as pathways of CRC developments

Deformation mapping of fibronectin fibrils using digital image correlation

Title from PDF of title page, viewed on January 9, 2012Thesis advisor: Ganesh ThiagarajanVitaIncludes bibliographic references (p. 109-110)Thesis (M.S.)--School of Computing and Engineering. University of Missouri Kansas City, 2012Bone cells produce large amounts of extracellular matrix (ECM) proteins that form a fibrillar scaffold on which bone mineral is deposited. Prior work has shown that fibronectin fibrils are one of the earliest ECM proteins to be assembled. Time lapse imaging techniques show that the deposition of fibronectin by osteoblasts is a highly dynamic process, in which the forming fibronectin fibril network is continually stretched, contracted and moved via the activity of motile cells. This study has developed an automated Digital Image Correlation based technique for determining the displacements and strains experienced by the fibrils during the assembly process. Fibril motion is tracked using a time lapse sequence of images and the motion kinematics are determined using an image cross-correlation method. The method is implemented in Matlab and compared to manual calculations. Furthermore, we have studied the motion of a set of 20 fibrils in order to predict fibril kinematics.Introduction -- Description of the program -- Results and observations -- Conclusion and future wor

ViWiD: Leveraging WiFi for Robust and Resource-Efficient SLAM

Recent interest towards autonomous navigation and exploration robots for indoor applications has spurred research into indoor Simultaneous Localization and Mapping (SLAM) robot systems. While most of these SLAM systems use Visual and LiDAR sensors in tandem with an odometry sensor, these odometry sensors drift over time. To combat this drift, Visual SLAM systems deploy compute and memory intensive search algorithms to detect `Loop Closures', which make the trajectory estimate globally consistent. To circumvent these resource (compute and memory) intensive algorithms, we present ViWiD, which integrates WiFi and Visual sensors in a dual-layered system. This dual-layered approach separates the tasks of local and global trajectory estimation making ViWiD resource efficient while achieving on-par or better performance to state-of-the-art Visual SLAM. We demonstrate ViWiD's performance on four datasets, covering over 1500 m of traversed path and show 4.3x and 4x reduction in compute and memory consumption respectively compared to state-of-the-art Visual and Lidar SLAM systems with on par SLAM performance

Randomized Phase III Trial Comparing Epirubicin/ Doxorubicin Plus Docetaxel and Epirubicin/ Doxorubicin Plus Paclitaxel as First Line Treatment in Women with Advanced Breast Cancer

This study aimed to examine the efficacy of docetaxel plus epirubicin against docetaxel plus capecitabine as first-line therapy for women with advanced breast cancer (ABC). Patients with ABC who had not been treated in the past were split into two groups: those who received docetaxel and epirubicin (DE) on day 1 and those who received docetaxel and capecitabine (DC) on day 1 and twice daily on days 1-14 of each 21-day cycle. Prior neoadjuvant treatment with anthracyclines was permitted if it had been finished more than a year prior to enrolment. The study\u27s major aim was to evaluate the difference in time to disease progression (TTP). Median TTP for DE was 10.6 months and for DC it was 11.0 months (P = 0.7), with each arm treating 170 women. Using the RECIST criterion, we found that the rates of complete responses were higher in DC (61%) than in DE (11%), and that the rates of partial responses were lower in DC (40%) than in DE (45%) (P = 0.8). Grade 3-4 neutropenia was more common with DE than DC (57% vs. 46%, P = 0.07), as were febrile neutropenia (11% vs. 8%, P = 0.4), hand-foot syndrome (0% vs. 4%, P = 0.02), grade 2-3 anemia (20% vs. 7%, P = 0.001), and asthenia (12% vs. 6%, P = 0.09)

Using mel‐frequency audio features from footstep sound and spatial segmentation techniques to improve frame‐based moving object detection

Moving object detection in video streams is a challenging and integral part of computer vision which is used in surveillance, traffic and site monitoring, and navigation. Compared with the background‐based techniques, frame differencing technique is computationally inexpensive. However, frame differencing technique only detects the boundary of a moving object. Due to changing light conditions, shadows, poor contrast between object and background, and a slow‐moving object, object detection rate from frame differencing technique reduces. This is because the number of noisy frames and frames with missing/partially detected object increases. Application of large kernel size morphological operations fails to remove noise as they might remove the boundary (or part) of a moving object. In this study, the authors propose a methodology to improve the frame differencing technique using footstep sound generated by a moving object. Audio recorded with the video system is processed and footstep sound is detected using audio features computed as mel‐frequency cepstral coefficients. Number of frames within each footstep sound are counted and processed. Spatial segmentation is used to find the moving object in noisy frames. A missing or partially detected object is recovered by modelling an ellipse using a moving object from other neighbourhood frames

A survey on blockchain in robotics:issues, opportunities, challenges and future directions

Abstract Robotics is the multi-disciplinary domain that is booming in today’s world, and expanding its roots deep into various fields of research, manufacturing industries, healthcare, and even in our day-to-day lives. Nevertheless, as with any other evolving technology, robotics face numerous challenges. In this context, lately, blockchain technology has been identified as a promising technology to resolve many of these issues such as identification of malicious/rogue nodes, malfunctioning/faults in automated processes, non-compliance to the agreed norms and privacy rules, security attacks on robotic systems, and non-transparency in performance monitoring and audits. In particular, blockchain with its features like decentrality, immutability, provenance, low operational cost, tight access control, and trustworthy operations, can offer significant improvements to new applications and use cases driven by robotics. Thus, the paper begins with exploring the key requirements and technical challenges encountered by robots in general. Next, it provides detailed overview of blockchain technology in a tutorial style. Then, the role of blockchain for different uses cases of robotics are surveyed. Furthermore, various technical challenges that need to be mitigated to harness full potential of blockchain for robotics are highlighted. Finally, the future research directions are presented that can pave the way ahead for advancements and profitable integration of blockchain in the realm of robotics.

A Pilot Study of Electrocardiographic Features in Patients with Obesity from a Tertiary Care Centre in Southern India (Electron)

Background: Obesity is associated with increased all-cause mortality and cardiovascular disease (CVD). An electrocardiogram (ECG) may be used to screen for subtle signs of CVD or altered cardiac morphology in the obese. Methodology: This observational cross-sectional analysed ECG changes in patients with obesity at a tertiary care centre in southern India. Results: One hundred and fifty adult patients with a mean (SD) BMI of 39.9 (6.7) kg/m2 were recruited in the study after excluding those with comorbidities (diabetes mellitus, systemic hypertension) or on chronic medications (ACE inhibitors). The cohort showed a female predominance (69.3%), with a mean (SD) age of 45.4 (11.2) years. Most patients exhibited a sinus rhythm (78%), with one patient showing features of first-degree conduction block. Sinus tachycardia was seen in 32 (21.3%) patients. We observed left and right ventricular hypertrophy in five (3.3%) and three (2%) patients, respectively. Observed ECG patterns included a prolonged QTc in 16 (10.7%) patients, inverted T-waves (mostly in the inferior leads) in 39 (26%) patients and ST-segment depression (predominantly in the lateral leads) in 14 (9.3%) patients. A greater prevalence was noted for morbid obesity. No deaths were reported in our cohort. Conclusions: The predominant ECG variations in this cohort included tachycardia, atrial enlargement, ventricular hypertrophy, conduction defects, LAD, features of ischemia or old infarction and repolarization abnormalities, with a greater prevalence in morbid obesity. Further studies are needed to assess the impact of weight reducing measures on reversibility of these changes and determine the association with outcomes in obese patients