Gilaki: From Language Regimes into Minoritizing

The effects of language contact depend on many different factors, such as language prestige, government and community support, people’s preference, linguistic proximity of the languages, among other things. As such, while there are some broad potentially predictable outcomes in situations of language contact, it is important to analyze each language contact situation in its own context. The aim of this study is to examine the maintenance and social function of Gilaki in the city of Lahijan located in the province Gilan, Iran. This study also poses the question whether Gilaki is at risk of becoming an endangered language. The participants (N=395), students at a language center and their families, completed a questionnaire with 36 questions. The participants were grouped according to gender, age, educational background, occupation, and spouse’s mother tongue based on a self-reported data collection style. The questionnaire, inspired by Parasher’s model (1980), examined the participants’ language use and preference in six social domains of family, friendship, neighborhood, transaction, education, and administration. The findings show statistically significant differences in the participants’ preference toward Persian in all six social domains. This study contributes to the body of work in language contact of lesser analyzed languages and sheds light on the trajectory of minoritized languages

Public school teachers’ perceptions of students’ diversity, cultural, and linguistic needs in the United States

  The need for culturally and linguistically sustaining teaching has become more apparent as school communities across the United States continually grow in cultural and linguistic diversity. This study investigated equity-based instruction for Culturally and Linguistically Diverse (CLD) students by examining public school teachers’ perceptions of preparation for diversity and inclusion of CLD students. A CLD research-based survey was designed and administered to 200 elementary and secondary school teachers in ten public schools in the United States. The study examined teachers’ perceptions, attitudes, self-awareness, and preparation toward CLD students’ cultural and linguistic needs. The analysis of the data uncovered evidence related to the themes of CLD instructional awareness and preparation in participants regarding their gender, race, age, ESL experience, highest degree, and years of teaching. The major findings of the study revealed the role of CLD-related training and awareness on the effectiveness of teacher preparation and their perceptions of the diversity of the students. The study concluded by providing implications for teachers, schools, educators, and policymakers on providing an equity-based educational environment for all students including the CLD ones

IMPACTS OF URBAN DEVELOPMENT PATTERN ON RUNOFF PEAK FLOWS AND STREAMFLOW FLASHINESS OF PERI-URBAN CATCHMENTS: ASSESSING THE PERFORMANCE OF PHYSICAL AND DATA-DRIVEN MODELS FOR REAL-TIME ENSEMBLE FLOOD FORECASTING

Urban growth is a global phenomenon, and the associated impacts on hydrology from land development are expected to increase, especially in peri-urban catchments, which are newly developing catchments in proximity of growing cities. In northern climates, hydrologic response of peri-urban catchments change with the water budget and climatic conditions. As a result, runoff response of northern peri-urban catchments can vary immensely across seasons. During warm seasons, the evapotranspiration (ET) and infiltration rates are high, so urban floods are expected to occur during high intensity, low duration storm events. During cold seasons and below freezing temperatures, surficial soils are typically frozen and nearly impervious. In addition, the ET rate is low throughout winter. Therefore, the difference in runoff response between peri-urban and natural catchments is least in winter. Furthermore, winter snow redistribution by plowing and endogenous urban heat affect the snowmelt timing and frequency. Due to the limited availability of data on snow removal and redistribution activities in northern peri-urban catchments, cold-season hydrologic modeling for peri-urban catchments remains a challenging task in urban hydrology. Research on the cold season hydrologic response of peri-urban catchments are mostly limited to Finland, Sweden, and Canada. The resulting research gap on seasonal change in hydrologic response of peri-urban catchments is common to many northern settings. In the first phase of this study, I use intensive discharge monitoring records at several peri-urban catchments near Syracuse, NY to calculate and compare seasonal runoff peak flows among several peri-urban catchments. These are selected to provide a range of drainage area and imperviousness to clarify the impact of urban development and catchment size on seasonal hydrologic behavior of peri-urban catchments. It is well understood that greater peak flows and higher stream flashiness are associated with increased surface imperviousness and storm location. However, the effect of the distribution of impervious areas on runoff peak flow response and stream flashiness of peri-urban catchments has not been well studied. In the second phase of this dissertation, I define a new geometric index, Relative Nearness of Imperviousness to the Catchment Outlet (RNICO), to correlate imperviousness distribution of peri-urban catchments with runoff peak flows and stream flashiness. The study sites for this phase of the study include ninety peri-urban catchments in proximity of 9 large US cities: New York, NY (NYC), Syracuse, NY, Baltimore, MD, Portland, OR, Chicago, IL, Austin, TX, Houston, TX, San Francisco, CA, and Los Angeles, CA. Based on RNICO, all development patterns are divided into 3 classes: upstream, centralized, and downstream. Analysis results showed an obvious increase in runoff peak flows and decrease in time to peak as the centroid of imperviousness moves downstream. This indicates that RNICO is an effective tool for classifying urban development patterns and for macroscale understanding of the hydrologic behavior of small peri-urban catchments, despite the complexity of urban drainage systems. Results for nine cities show strong positive correlations between RNICO and runoff peak flows and stream flashiness index for small peri-urban catchments. However, the area threshold used to distinguish small and large catchments differs slightly by location. For example, for Chicago, IL, NYC, NY, Baltimore, MD, Houston, TX, and Austin, TX area threshold values of 55, 40, 50, 42, and 32 km2 emerged, runoff peak flows in catchments with drainage area below these values were positively correlated to RNCIO. This first phase of this study suggests that RNICO is a stronger predictor of runoff peak flow and stream-flow regime in humid northern and southern US study sites, compared to more arid western US study sites. This difference is likely due to the greater precipitation rates and greater antecedent soil moisture contents for humid climates. The extent of urban infrastructure is less likely to control the effectiveness of RNICO for predicting runoff peak flows and R-B flashiness index for the selected study sites, due to the relatively similar urban development level within the peri-urban study catchments. Consistent forecast of peak flows across scales in flood hydrographs remains a challenge for most hydrologic models. Urbanization increases the magnitude and frequency of peak flows, often challenging the forecast ability for real-time flood prediction. Following advances in satellite and ground-based meteorological observations, global and continental real-time ensemble flood forecasting systems use a variety of physical hydrology models to predict urban peak flows. Artificial intelligence (AI) models provide an alternative approach to physical hydrology models for real-time flood forecasting. Despite recent advances in AI techniques for hydrologic prediction, ensemble stream-flow prediction by these methods has been limited. In addition, application of AI models for flood forecasting has been limited to large river basins, with very limited research on use of AI models for small peri-urban catchments. Flood forecasting in small urban catchments can be a critical task to urban safety due to the short time of concentration and quick precipitation runoff response. AI flood forecasting models typically apply upstream streamflow measurements to forecast downstream flood discharge. Therefore, the storm direction may change the flood travel time and time to peak, which challenges accurate flood forecasting. For example, if the storm direction is upstream through an AI model trained on the upstream gage data may fail to accurately predict peak flow magnitude and timing, at the outlet, this is due to the quicker runoff response of the downstream gage compared to the upstream station. There has been very limited focus on the impact of storm direction on peak flow response of urban catchments and available literature are limited to lab-scale prototypes and rainfall simulators. These may not fully represent real-world flooding scenarios. Therefore, the impact of storm direction on flood forecasting performance of peri-urban catchments is another important research gap in real-time urban flood forecasting. In the third phase of my dissertation project, I initially assess the impact of storm direction on the flood forecasting performance of an Adaptive Neuro Fuzzy Inference System (ANFIS) at a peri-urban catchment in proximity of Syracuse, NY. Next, I compare the relative utility of physical hydrology and AI approaches to predict flood hydrograph in peri-urban catchments. For this comparison, I selected ANFIS, and Sacramento Soil Moisture Accounting Model (SAC-SMA) for real-time ensemble re-forecasting of streamflow in several small to medium size suburban catchments near NYC for Hurricane Irene and a smaller storm event. The SAC-SMA model is a physical hydrology model that was initially developed by Burnash et al. (1973). The National Oceanic and Atmospheric Administration (NOAA) selected the SAC-SMA lumped model as a comparison baseline for participating distributed hydrologic models in the Distributed Model Intercomparison Project (DMIP), which aimed to identify the most suitable model for National Weather Service (NWS) streamflow prediction across the US (http://www.nws.noaa.gov/ohd/hrl/dmip/). More importantly, the NWS is currently using the lumped form of SAC-SMA for ensemble flood forecasting across the US (Emerton et al., 2016). For these reasons, I chose to employ a lumped version of SAC-SMA in my dissertation project. SAC-SMA performed well for both large and small events and for lead times of three to 24 hours, but ANFIS predicted the Hurricane Irene flood discharge well only for short lead times in small study catchments. ANFIS had reasonable percent bias (PBIAS) for predicting the small storm event for all lead times, indicating the utility of ANFIS for small events. In addition, the accuracy of both SAC-SMA and ANFIS models for ensemble flood prediction did not change significantly with catchment size and imperviousness. Overall, results of the third phase of this study suggest that the lumped SAC-SMA model may be a reliable option for local urban flood forecasting for evacuation plan lead time up to 24 hours. Due to the uncertainties in future climatic conditions, my study emphasizes the importance of using physical hydrology models for real-time flood forecasting of large events in small urban catchments. This recommendation is based on the finding that the performance of data-driven models may greatly decrease with the storm scale if the training period includes storms of magnitude less than storms in the validation period

Development of a fiber-based shape sensor for navigating flexible medical tools

Robot-assisted minimally invasive surgical procedure (RAMIS) is a subfield of minimally invasive surgeries with enhanced manual dexterity, manipulability, and intraoperative image guidance. In typical robotic surgeries, it is common to use rigid instruments with functional articulating tips. However, in some operations where no adequate and direct access to target anatomies is available, continuum robots can be more practical, as they provide curvilinear and flexible access. However, their inherent deformable design makes it difficult to accurately estimate their 3D shape during the operation in real-time. Despite extensive model-based research that relies on kinematics and mechanics, accurate shape sensing of continuum robots remains challenging. The state-of-the-art tracking technologies, including optical trackers, EM tracking systems, and intraoperative imaging modalities, are also unsuitable for this task, as they all have shortcomings. Optical fiber shape sensing solutions offer various advantages compared to other tracking modalities and can provide high-resolution shape measurements in real-time. However, commercially available fiber shape sensors are expensive and have limited accuracy. In this thesis, we propose two cost-effective fiber shape sensing solutions based on multiple single-mode fibers with FBG (fiber Bragg grating) arrays and eccentric FBGs. First, we present the fabrication and calibration process of two shape sensing prototypes based on multiple single-mode fibers with semi-rigid and super-elastic substrates. Then, we investigate the sensing mechanism of edge-FBGs, which are eccentric Bragg gratings inscribed off-axis in the fiber's core. Finally, we present a deep learning algorithm to model edge-FBG sensors that can directly predict the sensor's shape from its signal and does not require any calibration or shape reconstruction steps. In general, depending on the target application, each of the presented fiber shape sensing solutions can be used as a suitable tracking device. The developed fiber sensor with the semi-rigid substrate has a working channel in the middle and can accurately measure small deflections with an average tip error of 2.7 mm. The super-elastic sensor is suitable for measuring medium to large deflections, where a centimeter range tip error is still acceptable. The tip error in such super-elastic sensors is higher compared to semi-rigid sensors (9.9-16.2 mm in medium and large deflections, respectively), as there is a trade-off between accuracy and flexibility in substrate-based fiber sensors. Edge-FBG sensor, as the best performing sensing mechanism among the investigated fiber shape sensors, can achieve a tip accuracy of around 2 mm in complex shapes, where the fiber is heavily deflected. The developed edge-FBG shape sensing solution can compete with the state-of-the-art distributed fiber shape sensors that cost 30 times more

What is the Role of the Anti-Parasitic Drugs in the Treatment of Coronavirus Disease 2019?

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a rapidly emerging viral infection causing coronavirus disease 2019 (COVID-19). The first report of the novel coronavirus, SARS-CoV-2, originated in Wuhan, China, in early December 2019 . Currently, there are no U.S. Food and Drug Administration (FDA)–approved drugs for the treatment of patients with COVID-19. A great deal of effort is ongoing to find effective therapeutics and preventive measures against this transmissible virus with high mortality. As result, available data are limited, and there are minimal randomized controlled trial (RCT) data on the efficacy of antiviral or immunomodulatory agents for the treatment of COVID-19 . Most of the treatment protocols are based on observational studies and anecdotic reports

Instructional Design "Postpartum Fitness” for Midwife Staff of Shemiranat (Tehran, Iran) Health Network

Background: One of the postpartum cares lives is supporting and encouraging them more to exercise after delivery and monitoring them. Health care workers, particularly midwives have a great role in the promotion of sport activity. Purpose of this study is Designed training for "postpartum fitness" by Roth well approach for midwives at health network in Shemiranat.Materials and Methods: This research is kind of Instructional design. Sampling was done by using census method Data collection was done by multiple choice tests for knowledge and attitudes of questionnaire and practical assessment exercise was part. After assessment and instructional design and was done Roth well model and Ganyh strategies.Results: Average response to questions in the cognitive domain was 49%. In this study 92% of the employees have positive attitude to importance and impact of the study. The result of the data related to the workplace of participants is health centers (53.3%). Most frequency is for who has less than 5 years’ work experience (50%)and most frequency is for official staff (43.3%), most educational level related to bachelors (83.3%) and the highest age rate is between 30-40 years old (40%).Conclusion: Positive attitude towards this issue and earn score below %80 indicates a need for staff to learn and raise awareness about the above topic. Create knowledge, training, counseling mothers about this issue are the midwife duties. This reflects a greater emphasis on design education

Which Test to Perform for Cystic hydatic Diagnosis and When?

Echinococcosis is one of the 17 neglected tropical diseases (NTDs) recognized by the World Health Organization. The two major species of medical importance are Echinococcus granulosus and Echinococcus multilocularis (1).There are many studies about diagnostic method of hydatidosis, but there is still the question that which test to perform and when

Underseepage Control Measures at Painted Rock Dam

Painted Rock Dam, a 181 ft (55.2 m) high, zoned earth embankment detention structure near Gila Bend, Arizona, retained approximately 2.3 million acre ft (2.8 x 109m3) of water for an extended period during the winter of 1978- 1979. Several areas of seepage developed over major portions of the downstream valley and in a minor area on the right abutment. These areas were monitored while instrumentation was installed and investigations made to determine the nature of the seepage and provide the basis for evaluation of structural performance and design of necessary relief and control measures. Construction of seepage relief and control measures and stabilizing berms was accomplished in the fall of 1979. Performance of the project has been evaluated during subsequent storage periods through 1986, with the conclusion that the control measures are functioning satisfactorily, and in general accordance with design concepts. Site conditions, original design and construction, seepage observations, instrumentation, investigations, evaluations, and design and construction of remedial measures are summarized and lessons learned are presented