Browsing by Author "Moussa, Hanna (TTU)"
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Item A Novel Hybrid Method for Short-Term Wind Speed Prediction Based on Wind Probability Distribution Function and Machine Learning Models(2022) Dhakal, Rabin (TTU); Sedai, Ashish (TTU); Pol, Suhas (TTU); Parameswaran, Siva (TTU); Nejat, Ali (TTU); Moussa, Hanna (TTU)The need to deliver accurate predictions of renewable energy generation has long been recognized by stakeholders in the field and has propelled recent improvements in more precise wind speed prediction (WSP) methods. Models such as Weibull-probability-density-based WSP (WEB), Rayleigh-probability-density-based WSP (RYM), autoregressive integrated moving average (ARIMA), Kalman filter and support vector machines (SVR), artificial neural network (ANN), and hybrid models have been used for accurate prediction of wind speed with various forecast horizons. This study intends to incorporate all these methods to achieve a higher WSP accuracy as, thus far, hybrid wind speed predictions are mainly made by using multivariate time series data. To do so, an error correction algorithm for the probability-density-based wind speed prediction model is introduced. Moreover, a comparative analysis of the performance of each method for accurately predicting wind speed for each time step of short-term forecast horizons is performed. All the models studied are used to form the prediction model by optimizing the weight function for each time step of a forecast horizon for each model that contributed to forming the proposed hybrid prediction model. The National Oceanic and Atmospheric Administration (NOAA) and System Advisory Module (SAM) databases were used to demonstrate the accuracy of the proposed models and conduct a comparative analysis. The results of the study show the significant improvement on the performance of wind speed prediction models through the development of a proposed hybrid prediction model.Item Automated Detection and Scoring of Tumor-Infiltrating Lymphocytes in Breast Cancer Histopathology Slides(2023) Yosofvand, Mohammad (TTU); Khan, Sonia Y. (TTUHSC); Dhakal, Rabin (TTU); Nejat, Ali (TTU); Moustaid-Moussa, Naima (TTU); Rahman, Rakhshanda Layeequr (TTUHSC); Moussa, Hanna (TTU)Detection of tumor-infiltrating lymphocytes (TILs) in cancer images has gained significant importance as these lymphocytes can be used as a biomarker in cancer detection and treatment procedures. Our goal was to develop and apply a TILs detection tool that utilizes deep learning models, following two sequential steps. First, based on the guidelines from the International Immuno-Oncology Biomarker Working Group (IIOBWG) on Breast Cancer, we labeled 63 large pathology imaging slides and annotated the TILs in the stroma area to create the dataset required for model development. In the second step, various machine learning models were employed and trained to detect the stroma where U-Net deep learning structure was able to achieve 98% accuracy. After detecting the stroma area, a Mask R-CNN model was employed for the TILs detection task. The R-CNN model detected the TILs in various images and was used as the backbone analysis network for the GUI development of the TILs detection tool. This is the first study to combine two deep learning models for TILs detection at the cellular level in breast tumor histopathology slides. Our novel approach can be applied to scoring TILs in large cancer slides. Statistical analysis showed that the output of the implemented approach had 95% concordance with the scores assigned by the pathologists, with a p-value of 0.045 (n = 63). This demonstrated that the results from the developed software were statistically meaningful and highly accurate. The implemented approach in analyzing whole tumor histology slides and the newly developed TILs detection tool can be used for research purposes in biomedical and pathology applications and it can provide researchers and clinicians with the TIL score for various input images. Future research using additional breast cancer slides from various sources for further training and validation of the developed models is necessary for more inclusive, rigorous, and robust clinical applications.Item Combined effects of eicosapentaenoic acid and adipocyte renin–angiotensin system inhibition on breast cancer cell inflammation and migration(2020) Rasha, Fahmida (TTU); Kahathuduwa, Chanaka (TTU); Ramalingam, Latha (TTU); Hernandez, Arelys (TTU); Moussa, Hanna (TTU); Moustaid-Moussa, Naima (TTU)Obesity is a major risk factor for breast cancer (BC). Obesity-related metabolic alterations such as inflammation and overactivation of the adipose renin–angiotensin system (RAS) may contribute to the progression of BC. Clinically used antihypertensive drugs such as angiotensin-converting enzyme inhibitors (ACE-I) and dietary bioactive components such as eicosapentaenoic acid (EPA) are known for their anti-inflammatory and adipose RAS blocking properties. However, whether EPA enhances the protective effects of ACE-I in lessening adipocyte inflammation on BC cells has not been studied. We hypothesized that combined EPA and ACE-I would attenuate BC cell inflammation and migration possibly via adipose RAS inhibition. To test our hypothesis, we examined the (i) direct effects of an ACE-I (captopril (CAP)) or EPA, individually and combined, on MCF-7 and MDA-MB-231 human BC cells, and the (ii) effects of conditioned medium (CM) from human adipocytes pretreated with the abovementioned agents on BC cells. We demonstrated that CM from adipocytes pretreated with EPA with or without captopril (but not direct treatments of BC cells) significantly reduced proinflammatory cytokines expression in both BC cell lines. Additionally, cell migration was reduced in MDA-MB-231 cells in response to both direct and CM-mediated CAP and/or EPA treatments. In summary, our study provides a significant insight into added benefits of combining anti-inflammatory EPA and antihypertensive ACE-I to attenuate the effects of adipocytes on breast cancer cell migration and inflammation.Item Development and Application of MAGIC-f Gel in Cancer Research and Medical Imaging(2021) Dhakal, Rabin (TTU); Yosofvand, Mohammad (TTU); Moussa, Hanna (TTU)Much of the complex medical physics work requires radiation dose delivery, which requires dosimeters to accurately measure complex three-dimensional dose distribution with good spatial resolution. MAGIC-f polymer gel is one of the emerging new dosimeters widely used in medical physics research. The purpose of this study was to present an overview of polymer gel dosimetry, using MAGIC-f gel, including its composition, manufacture, imaging, calibration, and application to medical physics research. In this review, the history of polymer gel development is presented, along with the applications so far. Moreover, the most important experiments/applications of MAGIC-f polymer gel are discussed to illustrate the behavior of gel on different conditions of irradiation, imaging, and manufacturing techniques. Finally, various future works are suggested based on the past and present works on MAGIC-f gel and polymer gel in general, with the hope that these bits of knowledge can provide important clues for future research on MAGIC-f gel as a dosimeter.Item Effects of curcumin in a mouse model of very high fat diet-induced obesity(2020) Koboziev, Iurii (TTU); Scoggin, Shane (TTU); Gong, Xiaoxia (TTU); Mirzaei, Parvin (TTU); Zabet-Moghaddam, Masoud (TTU); Yosofvand, Mohammad (TTU); Moussa, Hanna (TTU); Jones-Hall, Yava; Moustaid-Moussa, Naima (TTU)Worldwide rates of Western-diet-induced obesity epidemics are growing dramatically. Being linked with numerous comorbidities and complications, including cardiovascular disease, type 2 diabetes, cancer, chronic inflammation, and osteoarthritis (OA), obesity represents one of the most threatening challenges for modern healthcare. Mouse models are an invaluable tool for investigating the effects of diets and their bioactive components against high fat diet (HFD)-induced obesity and its comorbidities. During recent years, very high fat diets (VHFDs), providing 58–60% kcal fat, have become a popular alternative to more traditional HFDs, providing 40–45% total kcal fat, due to the faster induction of obesity and stronger metabolic responses. This project aims to investigate if the 60% fat VHFD is suitable to evaluate the protective effects of curcumin in dietinduced obesity and osteoarthritis. B6 male mice, prone to diet-induced metabolic dysfunction, were supplemented with VHFD without or with curcumin for 13 weeks. Under these experimental conditions, feeding mice a VHFD for 13 weeks did not result in expected robust manifestations of the targeted pathophysiologic conditions. Supplementing the diet with curcumin, in turn, protected the animals against obesity without significant changes in white adipocyte size, glucose clearance, and knee cartilage integrity. Additional research is needed to optimize diet composition, curcumin dosage, and duration of dietary interventions to establish the VHFD-induced obesity for evaluating the effects of curcumin on metabolic dysfunctions related to obesity and osteoarthritis.Item Enhanced Metabolic Effects of Fish Oil When Combined with Vitamin D in Diet-Induced Obese Male Mice(2024) Ramalingam, Latha (TTU); Mabry, Brennan (TTU); Menikdiwela, Kalhara R. (TTU); Moussa, Hanna (TTU); Moustaid-Moussa, Naima (TTU)Vitamin D (vit D) and fish oil (FO) both offer unique health benefits, however, their combined effects have not been evaluated in obesity and nonalcoholic fatty liver disease (NAFLD). Hence, we hypothesized that vit D and FO supplementation would have additive effects in reducing obesity-associated inflammation and NAFLD. Male C57BL6 mice were split into four groups and fed a high fat (HF) diet supplemented with a low (HF; +200 IU vit D) or high dose of vitamin D (HF + D; +1000 IU vit D); combination of vit D and FO (HF-FO; +1000 IU vit D); or only FO (HF-FO; +200 IU vit D) for 12 weeks. We measured body weight, food intake, glucose tolerance, and harvested epididymal fat pad and liver for gene expression analyses. Adiposity was reduced in groups supplemented with both FO and vit D. Glucose clearance was higher in FO-supplemented groups compared to mice fed HF. In adipose tissue, markers of fatty acid synthesis and oxidation were comparable in groups that received vit D and FO individually in comparison to HF. However, the vit D and FO group had significantly lower fatty acid synthesis and higher oxidation compared to the other groups. Vit D and FO also significantly improved fatty acid oxidation, despite similar fatty acid synthesis among the four groups in liver. Even though we did not find additive effects of vit D and FO, our data provide evidence that FO reduces markers of obesity in the presence of adequate levels of vit D.Item Mice with humanized immune system as novel models to study HIV-associated pulmonary hypertension(2022) Rodriguez-Irizarry, Valerie J. (TTUHSC); Schneider, Alina C. (TTUHSC); Ahle, Daniel (TTUHSC); Smith, Justin M.; Suarez-Martinez, Edu B.; Salazar, Ethan A. (TTUHSC); McDaniel Mims, Brianyell (TTUHSC); Rasha, Fahmida (TTUHSC); Moussa, Hanna (TTU); Moustaid-Moussa, Naima (TTU); Pruitt, Kevin (TTUHSC); Fonseca, Marcelo; Henriquez, Mauricio; Clauss, Matthias A.; Grisham, Matthew B. (TTUHSC); Almodovar, Sharilyn (TTUHSC)People living with HIV and who receive antiretroviral therapy have a significantly improved lifespan, compared to the early days without therapy. Unfortunately, persisting viral replication in the lungs sustains chronic inflammation, which may cause pulmonary vascular dysfunction and ultimate life-threatening Pulmonary Hypertension (PH). The mechanisms involved in the progression of HIV and PH remain unclear. The study of HIV-PH is limited due to the lack of tractable animal models that recapitulate infection and pathobiological aspects of PH. On one hand, mice with humanized immune systems (hu-mice) are highly relevant to HIV research but their suitability for HIV-PH research deserves investigation. On another hand, the Hypoxia-Sugen is a well-established model for experimental PH that combines hypoxia with the VEGF antagonist SU5416. To test the suitability of hu-mice, we combined HIV with either SU5416 or hypoxia. Using right heart catheterization, we found that combining HIV+SU5416 exacerbated PH. HIV infection increases human pro-inflammatory cytokines in the lungs, compared to uninfected mice. Histopathological examinations showed pulmonary vascular inflammation with arterial muscularization in HIV-PH. We also found an increase in endothelial-monocyte activating polypeptide II (EMAP II) when combining HIV+SU5416. Therefore, combinations of HIV with SU5416 or hypoxia recapitulate PH in hu-mice, creating well-suited models for infectious mechanistic pulmonary vascular research in small animals.Item Renewable energy resource assessment for rural electrification: a case study in Nepal(2023) Sedai, Ashish (TTU); Dhakal, Rabin; Koirala, Pranik; Gautam, Shishir; Pokhrel, Rajat; Lohani, Sunil Prasad; Moussa, Hanna (TTU); Pol, Suhas (TTU)Renewable energy could mitigate remote area energy crises through rural electrification. Karnali province, one of the seven federal provinces of Nepal, is such a remote location and is most deprived in terms of electricity access. Around 67% of the population of the Karnali province is not connected to the national grid electricity supply. High altitude, mountainous topography makes it difficult to provide grid access to the region. This study summarizes the current electricity access status in Nepal and Karnali province specifically. The paper discusses the energy, economic and environmental (3E) analysis of different renewable energy resources like solar and wind energy for the grid-isolated region in Mugu and Jumla district of Karnali province. The study investigates the feasibility of a 200-kW solar power plant installation in Gamghadi, the capital of Mugu district and a 100-kW wind power plant installation in Tila village, Jumla district. The study suggests whether a similar installation of the distributed energy plant is a solution to mitigate the energy crisis problem in the high Himalayas regions, like Karnali province of Nepal. Based on the high-level resource assessment, the study estimates an investment cost ranging from 7 to 9 million USD would be necessary for the installation of such distributed solar PV and wind turbines.Item Review of Biological Effects of Acute and Chronic Radiation Exposure on Caenorhabditis elegans(2021) Dhakal, Rabin (TTU); Yosofvand, Mohammad (TTU); Yavari, Mahsa (TTU); Abdulrahman, Ramzi; Schurr, Ryan; Moustaid-Moussa, Naima (TTU); Moussa, Hanna (TTU)Knowledge regarding complex radiation responses in biological systems can be enhanced using genetically amenable model organisms. In this manuscript, we reviewed the use of the nematode, Caenorhabditis elegans (C. elegans), as a model organism to investigate radiation’s biological effects. Diverse types of experiments were conducted on C. elegans, using acute and chronic exposure to different ionizing radiation types, and to assess various biological responses. These responses differed based on the type and dose of radiation and the chemical substances in which the worms were grown or maintained. A few studies compared responses to various radiation types and doses as well as other environmental exposures. Therefore, this paper focused on the effect of irradiation on C. elegans, based on the intensity of the radiation dose and the length of exposure and ways to decrease the effects of ionizing radiation. Moreover, we discussed several studies showing that dietary components such as vitamin A, polyunsaturated fatty acids, and polyphenol-rich food source may promote the resistance of C. elegans to ionizing radiation and increase their life span after irradiation.Item Solar Particle Event Dose Forecasting Using Regression Techniques(2018) Lovelace, Alan Mitchel (TTU); Rashid, Al Maqsudur (TTU); de Wet, Wouter C.; Townsend, Lawrence W.; Wesley Hines, J.; Moussa, Hanna (TTU)Doses from solar particle events can be a serious threat to the wellbeing of crews traveling through space. Therefore, methods for predicting the time such events will take place, methods for forecasting the dose buildup over time, and methods for forecasting the potential total dose from such events are needed to enable crews to take actions to mitigate the effects by entering a shielded area designed for their protection. This work focuses on forecasting the total dose expected for an event, based upon doses obtained very early in the event, using the kernel regression method. The model uses tables of calculated doses for historical solar particle events augmented with hypothetical events similar to the actual ones for training purposes. Reasonably accurate predictions of the total dose expected for an event can be made within the first hour after event onset. Predictive accuracies generally increase as the event progresses in time. The only inputs required are doses and times since event onset as provided by dosimetry devices. One hundred thirteen actual events with total doses between 1 and 1,000 cGy were tested using the model. At 1 hr into the event, total dose predictions were within ±30% of the actual total doses for 91 events (81%) and within ±15% for 54 of them (48%). Within the first 4 hr following event onset, total dose predictions were within ±30% for 98 events (87%) and within ±15% for 66 of them (58%). A software package implementing the model has been provided to the Space Radiation Analysis Group at NASA Johnson Space for incorporation into their operational procedures for analyzing possible threats to space crews from solar particle events.Item Wind energy as a source of green hydrogen production in the USA(2023) Sedai, Ashish (TTU); Dhakal, Rabin (TTU); Gautam, Shishir; Kumar Sedhain, Bijaya; Singh Thapa, Biraj; Moussa, Hanna (TTU); Pol, Suhas (TTU)The study incorporates an overview of the green hydrogen-production potential from wind energy in the USA, its application in power generation and the scope of substituting grey and blue hydrogen for industrial usage. Over 10 million metric tons of grey and blue hydrogen is produced in the USA annually to fulfil the industrial demand, whereas, for 1 million metric tons of hydrogen generated, 13 million metric tons of CO2 are released into the atmosphere. The research aims to provide a state-of-the-art review of the green hydrogen technology value chain and a case study on the production of green hydrogen from an 8-MW wind turbine installed in the southern plain region of Texas. This research estimates that the wind-farm capacity of 130 gigawatt-hours is required to substitute grey and blue hydrogen for fulfilling the current US annual industrial hydrogen demand of 10 million metric tons. The study investigates hydrogen-storage methods and the scope of green hydrogen-based storage facilities for energy produced from a wind turbine. This research focuses on the USA's potential to meet all its industrial and other hydrogen application requirements through green hydrogen.