Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing

Wind serves as natural resources as the solution to minimize global warming and has been commonly used to produce electricity. Because of their uncontrollable wind characteristics, wind speed forecasting is considered one of the best challenges in developing power generation. The Autoregressive Integrated Moving Average (ARIMA), Simple Exponential Smoothing (SES) and a hybrid model combination of ARIMA and SES will be used in this study to predict the wind speed. The mean absolute percentage error (MAPE) and the root mean square error (RMSE) are used as measurement of efficiency. The hybrid model provides a positive outcome for predicting wind speed compare to the single model of ARIMA and SES

Carcinoma of sigmoid colon following urinary diversion: a case report and review of literature

BACKGROUND: The association of ureterosigmoidostomy with colonic cancer is well established. A 100-fold increased risk of malignancy has been proposed in association with ureterosigmoidostomy. Characteristically there is a latent period of around 20–30 years before the occurrence of cancer. CASE PRESENTATION: An unusual case of adenocarcinoma of the colon in a 36-year-old patient is presented. The patient underwent three operations in his infancy for exstrophy but after failure to close bladder, ureterosigmoidostomy was attempted at the age of 5 years and was converted to an ileal conduit after 8 months. At the age of 36 years, 30 years following ileal conduit urinary diversion for exstrophy, he presented in emergency with large bowel obstruction due to adenocarcinoma of the sigmoid colon. CONCLUSION: Patients who undergo urinary diversion for exstrophy may be kept on a regular follow-up surveillance colonoscopy as most of these young adults may later present with vague abdominal symptoms which may not be taken seriously until they increase to an extent as to present with intestinal obstruction as in the present case

Quantification of Ion Migration in CH3NH3PbI3 Perovskite Solar Cells by Transient Capacitance Measurements

Solar cells based on organic-inorganic metal halide perovskites show efficiencies close to highly-optimized silicon solar cells. However, ion migration in the perovskite films leads to device degradation and impedes large scale commercial applications. We use transient ion-drift measurements to quantify activation energy, diffusion coefficient, and concentration of mobile ions in methylammonium lead triiodide (MAPbI3) perovskite solar cells, and find that their properties change close to the tetragonal-to-orthorhombic phase transition temperature. We identify three migrating ion species which we attribute to the migration of iodide (I-) and methylammonium (MA+). We find that the concentration of mobile MA+ ions is one order of magnitude higher than the one of mobile I- ions, and that the diffusion coefficient of mobile MA+ ions is three orders of magnitude lower than the one for mobile I- ions. We furthermore observe that the activation energy of mobile I- ions (0.29 eV) is highly reproducible for different devices, while the activation energy of mobile MA+ depends strongly on device fabrication. This quantification of mobile ions in MAPbI3 will lead to a better understanding of ion migration and its role in operation and degradation of perovskite solar cells

A Novel Approach to Railway Track Faults Detection Using Acoustic Analysis.

Regular inspection of railway track health is crucial for maintaining safe and reliable train operations. Factors, such as cracks, ballast issues, rail discontinuity, loose nuts and bolts, burnt wheels, superelevation, and misalignment developed on the rails due to non-maintenance, pre-emptive investigations and delayed detection, pose a grave danger and threats to the safe operation of rail transport. The traditional procedure of manually inspecting the rail track using a railway cart is both inefficient and prone to human error and biases. In a country like Pakistan where train accidents have taken many lives, it is not unusual to automate such approaches to avoid such accidents and save countless lives. This study aims at enhancing the traditional railway cart system to address these issues by introducing an automatic railway track fault detection system using acoustic analysis. In this regard, this study makes two important contributions: data collection on Pakistan railway tracks using acoustic signals and the application of various classification techniques to the collected data. Initially, three types of tracks are considered, including normal track, wheel burnt and superelevation, due to their common occurrence. Several well-known machine learning algorithms are applied such as support vector machines, logistic regression, random forest and decision tree classifier, in addition to deep learning models like multilayer perceptron and convolutional neural networks. Results suggest that acoustic data can help determine the track faults successfully. Results indicate that the best results are obtained by RF and DT with an accuracy of 97%

Restoring mitofusin balance prevents axonal degeneration in a Charcot-Marie-Tooth type 2A model

Mitofusin-2 (MFN2) is a mitochondrial outer-membrane protein that plays a pivotal role in mitochondrial dynamics in most tissues, yet mutations in MFN2, which cause Charcot-Marie-Tooth disease type 2A (CMT2A), primarily affect the nervous system. We generated a transgenic mouse model of CMT2A that developed severe early onset vision loss and neurological deficits, axonal degeneration without cell body loss, and cytoplasmic and axonal accumulations of fragmented mitochondria. While mitochondrial aggregates were labeled for mitophagy, mutant MFN2 did not inhibit Parkin-mediated degradation, but instead had a dominant negative effect on mitochondrial fusion only when MFN1 was at low levels, as occurs in neurons. Finally, using a transgenic approach, we found that augmenting the level of MFN1 in the nervous system in vivo rescued all phenotypes in mutant MFN2R94Q-expressing mice. These data demonstrate that the MFN1/MFN2 ratio is a key determinant of tissue specificity in CMT2A and indicate that augmentation of MFN1 in the nervous system is a viable therapeutic strategy for the disease

Prosthetic stent graft infection after endovascular abdominal aortic aneurysm repair

ObjectiveThe purpose of this report is to discuss the incidence, diagnosis, and management of stent graft infections after endovascular aneurysm repair (EVAR).MethodsData were collected from the hospital database and medical case notes for all patients with infected endografts after elective or emergency EVAR for abdominal aortic aneurysm (AAA) during the last 8 years in two university teaching hospitals in Northern Ireland. The data included the patient’s age, gender, presentation of sepsis, treatment offered, and the ultimate outcome. The diagnosis of graft-related sepsis was established by a combination of investigations including inflammatory markers, labelled white cell scan, computed tomography (CT) scan, microbiology cultures, and postmortem examination.ResultsGraft-related septic complications occurred in six of 509 patients, including 433 elective repairs and 76 emergency endografts for ruptured AAA. Two patients presented with left psoas abscess and were treated successfully with extra-anatomic bypass and removal of the infected stent graft. Two more patients presented with infected graft without other evidence of intra-abdominal sepsis: one underwent successful removal of the infected prosthesis with extra-anatomical bypass, and the other was treated conservatively and died of progressively worsening sepsis. The fifth patient presented with unexplained fever and died suddenly, with a postmortem diagnosis of aortoenteric fistula and ruptured aneurysm. The last patient presented with an aortoenteric fistula, was treated conservatively in view of concurrent myelodysplasia, and died of possible aneurysm rupture.ConclusionThis report emphasizes the need for continued awareness of potential graft-related septic complications in patients undergoing EVAR of AAA. Attention to detail with regard to sterility and antibiotic prophylaxis during stent grafting and during any secondary interventions is vital in reducing the risk of infection. In addition, early recognition and prompt treatment are essential for a successful outcome

Dual Axis Solar Tracker System Application Based on Arduino Atmega 2560 and Internet of Things (iot) for Submersible Pump Operation

Most of the Solar Power Plants (PLTS) still use a static system which is considered less effective in absorbing solar energy. This is due to the earth's rotation which causes the sun to not always be in the same position. In order to optimize the absorption of solar energy so that the power produced is stable and maximum, a tracking system is applied to the solar panels. This tool works by using 4 LDR sensors and 2 DC Power Window motors as the driving force and the presence of Wi-Fi as a communication medium between the Arduino ATmega 2560 and the Android application so that the performance of the solar tracker can be monitored via a smartphone in real time. The purpose of this research is to optimize the efficiency of solar panels. The method used in this research is Research and Development (R&D). The test was carried out with the Dual Axis Solar Tracker system against a load in the form of a submersible pump. The test results show the average efficiency of the Dual Axis Solar Tracker system is 20.89% with an average power output of 84.81%

Locating nidi for high-frequency chest wall oscillation smart therapy via acoustic imaging of lung airways as a spatial network

High-frequency chest wall oscillation (HFCWO) therapy is one of the techniques to facilitate the draining of a patient’s lung secretion in pathological situations, and smart therapy with HFCWO devices equipped with multiple actuators can be achieved via locating nidi in the lung. In this paper, through developing a novel acoustic lung spatial model and utilizing acoustic imaging simulation, a new and effective method for assessing lung function with acoustic imaging is presented, which links acoustic lung images with pathologic changes. The structural similarity between the acoustic reference image based on actual lung sound and our model acoustic image based on the airway impedance was achieved by an index of 0.8987, with 1 as the exact score. Simulation studies based on the model are used to analyze the practicality and the extreme design of the acoustic imaging system on the resolution of the located nidus. For instance, a practical system design with sensor numbers between 4 and 35 may recognize a lower resolution nidus length of 73 mm to a better resolution nidus length of 22 mm. On the other hand, an extreme system design with more than 1000 sensors can recognize greater nidus resolution at under 10 mm. Additionally, this research may be utilized to offer recommendations for acoustic imaging system design and assess the number of sensors and sensing diameter in current acoustic imaging systems. Furthermore, the geographic detection of nidus length allows for analyzing of HFCWO therapy results

An acoustic system of sound acquisition and image generation for frequent and reliable lung function assessment

Lung sounds can be translated into acoustic imaging as an alternative to standard imaging to assess lung function frequently for improved therapy efficiency. This study proposes a comprehensive acoustic lung imaging system translated from acquired lung sounds for continual and reliable lung function assessment in response to the growing clinical interest in frequent lung function assessment. The proposed system comprises subsystems, such as data acquisition, signal processing, and imaging algorithm. This study demonstrated the design and implementation of a robust lung sound acquisition and imaging system using microelectromechanical microphones that reduce external noise contamination through redesigned hardware and dynamic signal processing. Regarding lung signal acquisition, the proposed system accomplished better root mean square error (RMSE) by around 0.15 and signal-to-noise ratio (SNR) by about 7 dB compared to commercial digital stethoscopes. RMSE and SNR reflect the accuracy in capturing desired signals and robustness-to-noise contamination and are used to quantitatively compare the system data acquisition to the commercially available acoustic and electronic devices in a noisy setting. The proposed system’s sensor position is neutral when representing lung signals, with a signal power loss ratio of around 5 dB compared to 10 dB from digital stethoscopes, in terms of the sensor area sensing sensitivity power spectrum mapping. The proposed system obtains about 7%–12% of more accurate detection of the actual nidus length than digital stethoscopes through imaging translated from acquired lung signals. Additionally, the detected airway obstruction results agree closely (91%) with airway remodeling studies