Showing papers by "San Diego State University published in 2023"

Embracing Disability Culture in Schools

Abstract: This viewpoint will expose readers to disability as a social construct shaped by power and oppression, not an individual medical issue defined by diagnosis. As professionals, we are doing a disservice if we continue to silo the disability experience to the limits of service delivery. We must intentionally seek ways to challenge how we think, view, and respond to disability to ensure that our approach is consistent with the current needs of the disability community.Specific practices related to accessibility and universal design will be highlighted. Strategies to embrace disability culture will be discussed as it is vital to bridge the gap between school and community.

Effects of Mixed Nut Consumption on Blood Glucose, Insulin, Satiety, and the Microbiome in a Healthy Population: A Pilot Study

Abstract: Nuts contain many health-promoting nutrients, fiber, and phytochemicals. Nut consumption has been reported to improve several chronic disease risk factors. Most studies to date have investigated single variety nut consumption. A nut mixture may offer a more diverse array of nutrients over single variety nuts. The primary outcome of this study was to examine the effects of mixed nut consumption on postprandial glucose, insulin, and satiety in healthy young adults. Exploratory outcomes include the effects of daily nut consumption on stool microbiome and bowel movement patterns. Twenty participants were randomized to consume either 42 g of mixed nuts or 46 g of potato chips daily for 3 weeks. Mixed nut consumption did not alter postprandial blood glucose and insulin, while potato chip consumption increased glucose and insulin (P < .05). There were no significant differences in fasting blood glucose or insulin for either snack after 3 weeks of daily consumption. Both snacks increased satiety while there were no significant differences in body weight, body fat, blood pressure, waist-to-hip ratio, or anxiety. After 3 weeks of snack consumption, both groups significantly reduced straining during bowel movements while the mixed nut group slightly increased stool amount. There were no significant changes in microbiome composition for either group; however, there was a nonsignificant trend toward increased Firmicutes to Bacteroidetes ratio in the potato chip group and an opposite trend in the mixed nut group. The results of this study suggest that mixed nuts are a healthy alternative for blood sugar control. The study was registered at ClinicalTrials.gov, Number: NCT03375866.

Disentangling human influences on hydrological drought

Abstract: Human influences can both intensify or mitigate hydrological droughts significantly altering their severity, duration, and frequency via non-linear and dynamic feedbacks. Despite their large influence, current understanding of when, where and to what degree, human-water interactions modify hydrological drought is lacking. One of the key reasons for this is the scarce availability of quantitative human water use data as they are typically considered commercially sensitive and hard to obtain. Consequently, we often rely on static, low-resolution indicators of human water use (such as global water use databases) or qualitative information on human water use, when in reality human-water interactions are highly place-specific and non-stationary over time due to changes in water management and policies.In this study, we will disentangle human influences on hydrological droughts using observational hydro-meteorological and groundwater data and a unique dataset of spatially explicit, time-varying abstractions and discharges for a large sample of catchments across England. Building on recent work to quantify and detect human influences, we will use a suite of hydrological signatures to characterise deviations in droughts and low flows from a large sample of benchmark (i.e. near-natural) catchments. We will link these deviations to different characteristics of the abstractions data (e.g. seasonal catchment averages, abstraction purpose) and to key water management schemes (e.g. low flow alleviation schemes). In doing so, we will advance our current understanding of how humans influence hydrological droughts and how we can improve the collection of human-water use data for future environmental analyses.

Sign Production

Abstract: Sign languages provide crucial insights into what aspects of language production are affected by the motor systems used for production (the hands vs. the vocal tract) and by the perceptual systems engaged for comprehension (vision vs. audition). The discovery that sign languages have phonological structure (traditionally defined as the sound patterns of language) indicates important parallels between signing and speaking that constitute universal properties of language production. Psycholinguistic evidence that phonological assembly occurs during sign production includes slips of the hand, tip-of-the-fingers states, and form-based priming. Nonetheless, there are key differences between signing and speaking that illuminate how biology impacts language production: the use of multiple independent articulators, the impact of iconicity, the role of visual vs. auditory feedback, and the unique ability to code-blend (produce a word and a sign at the same time). Overall, the study of sign language production provides unique insights into factors that impact the language production system.

Beamforming Technique for Improving Physical Layer Security in an MIMO-OFDM Wireless Channel

Abstract: The open nature of the wireless medium leads to the growing technical literature on solutions and techniques for increasing the privacy and security of a wireless communication channel. This work focuses on implementing the beamforming technique incorporated with a combination of MIMO-OFDM techniques for increasing physical layer security in the downlink of a wireless communication channel. The rectangular antenna array has been employed at the Tx side of an MIMO-OFDM channel with two orthogonal polarizations. This results in an improvement in the downlink performance due to a reduction in a duration of the channel sounding procedure compared to its uplink counterpart. We have used the WINNER II module from MathWorks’ MATLAB to simulate a realistic wiretap channel including Alice (to represent a sender), Bobs (to represent users), and Eve (to represent the information leakage). We have numerically estimated the success rate of Eve and physical layer security with performing a beamforming technique, compared to the available techniques without any beamforming technique, in an MIMO-OFDM wireless channel. Although physical layer security is affected by power, we have demonstrated that the beamforming technique with the technique of assigning subcarriers for Bobs can significantly improve the physical layer security and thereby overcome information leakage in the wiretap channel.

Historical dynamics of terrestrial carbon during 1901–2016 as simulated by the CLM-Microbe model

Abstract: Abstract. The CLM-Microbe model was able to reproduce the variations of gross (GPP) and net (NPP) primary productivity, heterotrophic (HR), and soil (SR) respiration, microbial (MBC) biomass C in fungi (FBC) and bacteria (BBC) in the top 30 cm and 1 m, dissolved (DOC) and soil organic C (SOC) in the top 30 cm and 1 m during 2901–2016. During the study period, simulated C variables increased by approximately 30 PgC yr−1 for GPP, 13 PgC yr−1 for NPP, 12 PgC yr−1 for HR, 25 PgC yr−1 for SR, 1.0 PgC for FBC and 0.4 PgC for BBC in 0–30 cm, 1.2 PgC for FBC, 0.7 PgC for BBC, 2.4 PgC for DOC, 34 PgC for SOC, and 4 PgC for litter C in 0–1 m, and 37 PgC for vegetation C. Increases in C fluxes and pools were larger at northern high latitudes and in equatorial regions than at other latitudes; the largest absolute increases of C fluxes and pools were in Asia and South America, particularly in eastern Asia and central and northern South America. However, the largest relative increases of GPP, NPP, HR, and SR in Asia and Europe, FBC (0–30 cm and 0–1 m) in South America, BBC (0–30 cm and 0–1 m) in Europe, DOC (0–1 m) in South America and Europe, SOC (0–1 m) in Africa, and vegetation C and litter C (0–1 m) in Europe. Vegetation productivity was primarily controlled by warming and precipitation, while microbial and soil C was jointly governed by vegetation C input and soil temperature and moisture. This study enhances our understanding of soil microbial roles in the global terrestrial C cycle.

Cultural intelligence as key competency for inclusion in diverse workgroups and organizations

Abstract: Increasing diversity in workgroups and workplaces has accentuated the importance of inclusion, allowing organizations to leverage diversity such that distinct perspectives and approaches are recognized and respected, flexibility and synergy are encouraged, information and resources are equitably available, and everyone can contribute. In this chapter, I make a case that the very concept of inclusion in diverse workgroups and workplaces might be viewed and enacted differently by diverse members due to variations in their culturally-shaped perceptions and behaviors. Consequently, I propose that cultural intelligence (CQ) is a key competence that allows individuals to reconcile and leverage these variations in perceptions and behaviors to achieve greater inclusion in workgroups and organizations. CQ helps individuals to be aware of differences in perceptions and behaviors, adjust and regulate their perceptions and behaviors to fit diverse contexts, have flexibility and empathy to learn from interactions with different others, and contribute to organizational success. Implications for research and practice are discussed.

Arts-based practices for literacy &amp; language learning

Abstract: The arts serve many purposes in society. People communicate with and through the arts. Humans create art for pleasure and to make a statement. In fact, art is one of the things that makes us unique. While other animals can be taught to create art, they don't generally create art on their own. Of course, there is debate about this as some birds build elaborate nests and sing beautiful songs to their mates. But, in general, humans create art because we are compelled to do so. As reference.com notes, “Art influences society by changing opinions, instilling values and translating experiences across space and time. Research has shown art affects the fundamental sense of self. Painting, sculpture, music, literature and the other arts are often considered to be the repository of a society's collective memory” (https://www.reference.com/article/art-influence-society-466abce706f18fd0).

Using Machine Learning to Identify Hydrologic Signatures With an Encoder–Decoder Framework

Abstract: Hydrologic signatures are quantitative metrics that describe a streamflow time series. Examples include annual maximum flow, baseflow index and recession shape descriptors. In this paper, we use machine learning (ML) to learn encodings that are optimal ML equivalents of hydrologic signatures, and that are derived directly from the data. We compare the learned signatures to classical signatures, interpret their meaning, and use them to build rainfall-runoff models in otherwise ungauged watersheds. Our model has an encoder–decoder structure. The encoder is a convolutional neural net mapping historical flow and climate data to a low-dimensional vector encoding, analogous to hydrological signatures. The decoder structure includes stores and fluxes similar to a classical hydrologic model. For each timestep, the decoder uses current climate data, watershed attributes and the encoding to predict coefficients that distribute precipitation between stores and store outflow coefficients. The model is trained end-to-end on the U.S. CAMELS watershed data set to minimize streamflow error. We show that learned signatures can extract new information from streamflow series, because using learned signatures as input to the process-informed model improves prediction accuracy over benchmark configurations that use classical signatures or no signatures. We interpret learned signatures by correlation with classical signatures, and by using sensitivity analysis to assess their impact on modeled store dynamics. Learned signatures are spatially correlated and relate to streamflow dynamics including seasonality, high and low extremes, baseflow and recessions. We conclude that process-informed ML models and other applications using hydrologic signatures may benefit from replacing expert-selected signatures with learned signatures.

Overcoming an Evasion Attack on a CNN Model in the MIMO-OFDM Wireless Communication Channel

Abstract: Implementation of deep learning (DL)-based algorithms for wireless communication channels can drastically enhance the discrepancy between features and interference. However, the performance of DL-based algorithms can be degraded by multiple different attackers, whereby a DL-based model is subjected to adversarial input to purposefully and maliciously fool or defeat the DL-based model. To overcome an evasion attack, this work contributes toward implementing a channel coding technique, specifically convolutional channel coding, for improving a CNN model’s performance in a multi-input multi-output-orthogonal frequency-division multiplexing (MIMO-OFDM) wireless channel. In the preliminary stage, our CNN architecture has been trained by the mini-batch gradient descent algorithm, and we have achieved approximately 98% accuracy. In the presence of an evasion attack, we have deployed convolution channel coding for a CNN model in an MIMO-OFDM wireless channel. The effectiveness and performance of the model has been evaluated using the metrics BER, classification accuracy, physical layer security, and reliability, in the presence of an evasion attack. In the proposed model, a significant reduction in BERs has been obtained, and also a significant enhancement in wireless security in the presence of an evasion attack, which is accompanied by a robust and accurate wireless communication channel.

Optimizing Simultaneous Water Level and Wave Measurements From Multi‐GNSS Interferometric Reflectometry Over 1 Year at an Exposed Coastal Site

Abstract: Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) measures water level using the interference pattern in signal-to-noise ratio (SNR) from direct and reflected signals off the sea surface, retrieved from standard geodetic antennas. Significant wave height is also measured by determining the satellite elevation angles where reflections become incoherent. We developed an approach for standard geodetic antennas to simultaneously measure sea levels and waves using a criterion for identifying coherent reflections. We tested the method at an exposed coastal environment at the E.B. Scripps Memorial Pier in California. The 1-year test captures a broad range of sea states and benefits from several co-located standard oceanographic sensors. By including GPS, Galileo, and GLONASS observations, the retrieval rate increases by a factor of ∼2 over GPS alone. Uncorrected water levels are estimated with a root-mean-square (RMS) error of 18.2 cm with respect to a conventional tide gauge. We further developed a simplified correction to remove the effect of phenomena altering the SNR oscillatory frequency and phase, which reduces RMS errors to 9.4 cm. We estimate the significant wave height with 15 cm RMS error with respect to a traditional wave gauge. The method, however, requires a short calibration. We find the wave height errors increase abruptly beyond a fixed limit when high waves are present, that may be a result of the particular deployment geometry. With this caveat, the technology could be useful to deploy in under-sampled regions affected by compounded coastal hazards, such as in areas affected by tropical cyclones and flooding.

Nonlinear Dynamics Phenomenon in a Polydyne Cam with an Offset Flat Faced Follower Mechanism with Clearance

Abstract: Nonlinear response of the follower motion is simulated at different cam speeds, different coefficient of restitution, and different internal distance of the follower guide from inside. The nonlinear response of the follower is employed to investigate the chaotic phenomenon in cam follower system in the presence of follower offset. The numerical results are done using SolidWorks software. The chaos phenomenon is detected using Poincare’ maps with phase-plane portraits, the largest Lyapunov exponent parameter, and bifurcation diagram. The largest Lyapunov exponent has a maximum values when the follower offsets to the right, while the largest Lyapunov exponent has a minimum values when the follower offsets to the left. The chaotic phenomenon in cam follower system when the follower offsets to the left is more than the chaotic phenomenon when the follower offsets to the right.