University of Southern Mississippi

Transforming polyolefins (POs), such as polyethylene (PE), into vitrimers is a promising research field due to their low cost, high availability, and excellent chemical resistance and mechanical properties. In these...

According to the National Assessment of Educational Progress (NAEP), US reading and math scores have recently dropped. This decline is believed to be the result of the school closings that occurred during the COVID-19 pandemic. The drop likely contributed to the increase in pressure educators are feeling to teach in a way that leads to higher test scores. Unfortunately, one of the ways many teachers are assessed in the United States is according to how well their students perform on high-stakes standardized tests, which often provide misleading information on the extent to which students are learning. The passing of the Every Student Succeeds Act (ESSA) alleviated some of the problems associated with using these tests to evaluate student learning and the effectiveness of teachers. However, after ESSA was passed, some states have continued to use tests for these reasons. The United States is not the only nation that implements high-stakes standardized tests to evaluate the academic skills of students. Many other nations use this approach. In addition to frequently providing inaccurate information on student learning, this approach to assessment is harmful in other ways. This paper reminds policymakers how harmful this approach to assessment can be. It also provides details on how the use of performance assessments can improve the way student learning is evaluated in America and the rest of the world.

Agricultural consumer electronics, such as drones, sensors, and robotics, play a pivotal role in addressing challenges like wheat lodging, which can significantly impact crop yield and quality. This study leverages consumer-grade UAVs to classify wheat lodging types-root lodging and stem lodging-using high-resolution RGB images captured at three altitudes (15, 45, and 91 meters). By employing automatic segmentation techniques, datasets were generated for each altitude, and a refined EfficientNetV2-C model was proposed for classification. The model incorporates a Coordinate Attention (CA) mechanism to enhance feature extraction and Class-Balanced Focal Loss (CB-Focal Loss) to address data imbalance, achieving an average accuracy of 93.58%. This research highlights the integration of advanced AI-based classification with low-carbon agricultural drones, underscoring their relevance to consumer electronics. Compared to four conventional machine learning and two deep learning models, EfficientNetV2-C demonstrated superior performance at all altitudes while maintaining minimal carbon emissions. The study also examines the influence of UAV flight altitude on classification efficacy, revealing that while machine learning models were unaffected, deep learning models showed reduced performance at higher altitudes due to feature loss. These findings emphasize the potential of UAVs as accessible, scalable, and sustainable tools for real-time agricultural monitoring in precision farming.

Reverse genetic approaches are the standard in molecular biology to determine a protein’s function. Traditionally, nucleic acid targeting via gene knockout (DNA) and knockdown (RNA) has been the method of choice to remove proteins-of-interest. However, the nature of mammalian oocyte maturation and preimplantation embryo development can make nucleic acid targeting approaches difficult. Gene knockout allows time for compensatory mechanisms and secondary phenotypes to develop which can make interpretation of a protein’s function difficult. Furthermore, genes can be essential for animal and/or oocyte survival, and therefore, gene knockout is not always a viable approach to investigate oocyte maturation and preimplantation embryo development. Conversely, RNA-targeting approaches, ie RNA interference (RNAi) and morpholinos, rely on protein half-life and therefore are unable to knockdown every protein-of-interest. An increasing number of reverse genetic approaches that directly target proteins have been developed to overcome the limitations of nucleic acid-based approaches, including Trim-Away and auxin-inducible degradation. These protein-targeting approaches give researchers exquisite and fast control of protein loss. This review will discuss how Trim-Away and auxin-inducible degradation can overcome many of the challenges of nucleic acid based reverse genetic approaches. Furthermore, it highlights the unique research opportunities these approaches afford, such as targeting post-translationally modified proteins.

This article illustrates how science teachers can build upon the spatial repertoire within sheltered English instruction to support multilingual learners (MLs). Specifically, this work explores how multiple modalities within a secondary marine biology classroom can be leveraged for instruction to support language and content learning, as well as learners' participation in disciplinary practices. Through qualitative analysis of three classroom lessons, we highlight how a marine biology teacher drew on this spatial repertoire to support MLs use of language, content knowledge, and participation in science and engineering practices. Though content‐area teachers do not always view themselves as language teachers, this work serves as an example of how a science teacher augmented instruction to meet the needs of her MLs.

Purpose The purpose of this study was to evaluate the impact of a novel diabetes self-management education (DSME) intervention on self-reported behavioral and clinical outcomes. Methods Adults over the age of 35 with type 2 diabetes mellitus (T2DM) were recruited to participate in a 3-month study to assess the impact of the Live in Control intervention, a 4-week care supporter-integrated DSME program. Forty-nine participants and their care supporters participated in the program in a community setting. A prospective, repeated measure, pretest and posttest research design was employed with assessments at week 0 (W0; baseline), 4 weeks (W4), and 3 months (W12). The primary measures were diabetes-related self-management behaviors, self-efficacy, autonomy support, social support, distress, and A1C. Results Paired t -test analyses revealed significant changes in study variables across different time points. The self-management scores significantly improved from W0 to W4 and from W0 to W12. Self-efficacy significantly increased from W0 to W4 and from W0 to W12. Autonomy support significantly increased from W0 to W12, and social support scores significantly improved over the same period. Findings indicate that participants experienced enhanced support for themselves and from their social networks throughout the study. Diabetes-related distress significantly decreased from W0 to W12. Although decreases in A1C were not significant for the total study sample, those with A1C ≥8 had significant decreases from W0 to W12. Conclusions A care supporter-integrated DSME intervention can favorably impact diabetes self-care, perceived social support, and A1C, especially for those with higher A1C values, suggesting the positive impact of program participation.

Purpose Squamous cell carcinoma (SCC) at the anal canal (AC) site presents significant challenges in prognosis and treatment. Identifying key prognostic factors is essential for improving survival outcomes and guiding clinical decisions. This study aimed to evaluate demographic, clinical, and treatment-related factors influencing survival in SCC at the AC site, focusing on differences in sex and marital status. Methods We conducted a population-based cohort study utilizing the SEER cancer registry dataset. Kaplan Meier and Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for survival, adjusting for demographic and clinical factors. Stratified analyses were performed to examine sex-specific survival differences. A nomogram was developed to predict five-year survival probabilities. Results The cohort included 24,892 patients with SCC of the AC (median survival: 43 months, IQR: 16–97). Males had shorter survival (38 months, IQR: 13–92) than females (46 months, IQR: 17–100) had a higher mortality risk (HR: 1.66, 95% CI: 1.57–1.76, p<0.001). Married individuals had better survival outcomes (HR: 0.77, 95% CI: 0.72–0.82, p<0.001), while divorced/separated individuals had poorer prognosis (HR: 1.10, 95% CI: 1.03–1.18, p=0.005). Advanced-stage cancer significantly increased mortality risk, with distant-stage SCC showing the highest hazard ratio (HR: 3.22, 95% CI: 3.00–3.46, p<0.001). Chemotherapy, radiotherapy, and surgery significantly improved survival for the disease condition, where the nomogram demonstrated high predictive accuracy for five-year survival probabilities. Conclusion: Women and marital patients demonstrated better survival outcomes than their counterparts, while Non-White, advanced age, and cancer stages negatively affected survival. Surgery and chemotherapy significantly improved survival, highlighting existing disparities and warrants patient-centered, multimodal treatment strategies to improve quality of life for this disease condition.

Freshwater diversion may be implemented to restore coastal wetlands. With more freshwater coming into the estuarine systems, salinity decreases while nutrients and inundation increase. With salinity decreases, brackish marshes may transition to freshwater marshes or open water over time. However, research is generally lacking on how freshwater marsh plants can adapt to fluctuations of water levels, extended flooding, and elevated nutrients. Here we investigated the response of a dominant southeastern freshwater marsh species—Sagittaria lancifolia to inundation and nutrient addition. We built a marsh organ with six rows at different heights that underwent varying inundation durations. Each row had eight replicates with four randomly chosen for nitrogen fertilizer addition. We found that the end-of-season belowground biomass reached the maximum at around 85% of inundation while aboveground biomass increased with inundation, showing strong tolerance of inundation for this species. Fertilization did not impact biomass. However, the interaction between fertilization and percent inundation time was important in predicting leaf traits, including count, length, and width. Fertilized vegetation showed an increase of leaf count with inundation while control vegetation showed a decrease of leaf count with inundation. While both control and fertilized vegetation showed increase in leaf length and width with inundation, the increasing rate was greater in the fertilized vegetation, showing that fertilization helped leaves adapt to higher inundation more effectively. On the other hand, control vegetation showed a higher probability of flowering as the season continued, while fertilization reduced the likelihood that plants would produce flowers as the time went on, demonstrating the trade-offs that fertilization had on vegetation traits. This research will enhance our mechanistic understanding of how large-scale restoration activities that alter the biophysical environment could impact marsh vegetation.

We extend reasearch on employee narcissism by moving beyond its direct outcomes. Drawing from social exchange theory, we examine how supervisor supplication behavior influences the employee narcissism–LMX relationship. Our findings indicate that narcissists are less affected by the negative impact of supervisor supplication on LMX. Consequently, supervisor supplication weakens the negative indirect effect of employee narcissism on organizational citizenship behaviors via LMX. We test our hypotheses through an experimental study with 163 undergraduate students and a field study of 376 employee–supervisor dyads across a variety of industries. Our findings support the theoretical model, showing that individuals with high narcissism respond more favorably to supervisor supplication than those with low narcissism. Theoretical and practical implications are discussed.

Researchers have explored a variety of topics related to the finances of Hispanic-Serving Institutions (HSI), including how HSIs are funded and how HSI graduates fare in the labor market, including salary analyses. Related to staff and faculty, researchers have found that low salaries are a primary reason for faculty and staff to leave. However, no empirical work has explored whether there are salary inequities between staff and faculty working in HSIs and non-HSIs. As a result, this study leverages current Integrated Postsecondary Education Data System (IPEDS) data to explore salary differences between faculty (multiple ranks) and staff (multiple classifications) at HSIs and non-HSI peer institutions. Quantitative analyses suggest that HSI staff and faculty salaries are comparable with non-HSI salaries, yet controlling for institutional sector and level does reveal many salary inequities. Moreover, regression analyses reveal breakpoints when HSI salaries decrease as Hispanic student enrollment increases. Implications for research, policy, and practice are addressed, especially as they relate to federal funding mechanisms and private industry partnerships that could help provide HSIs with the financial support they deserve to compensate HSI faculty and staff, especially Latinx-identifying faculty and staff, equitably.

Societal decarbonization is essential for environmental sustainability and prosperity, requiring cohesive efforts to advance materials circularity alongside the development of zero-carbon energy and heat solutions. In most systems, these challenges...

Internal tides (ITs) are sub-surface gravity waves that generate significant sea surface height (SSH) signals detectable with satellite altimetry. The Surface Water Ocean Topography (SWOT) mission is capturing ocean surface data at an unprecedented spatial resolution of 2 km. Accurately identifying these IT signals is crucial for effectively monitoring other non-tidal oceanic signals. We use data-assimilative forecast system based on the HYbrid Coordinate Ocean Model (HYCOM) to identify both coherent and incoherent ITs and compared its performance with the state-of-the-art IT correction model (High Resolution Empirical Tide, HRET8.1). HYCOM demonstrated a 9% greater variance removal for coherent IT compared to HRET8.1 and eliminated an additional 14.6% of incoherent IT. Specifically, at the M$_2$ frequency, HYCOM removed 40-60% of coherent IT variance and 10-20% of incoherent IT variance. Ocean forecast models like HYCOM enhance our understanding of IT dynamics and serve as alternative tools for IT mapping and altimetry correction.

Observing air-sea interactions on a global scale is essential for improving Earth system forecasts. Yet these exchanges are challenging to quantify for a range of reasons, including extreme conditions, vast and remote under-sampled locations, requirements for a multitude of co-located variables, and the high variability of fluxes in space and time. Uncrewed Surface Vehicles (USVs) present a novel solution for measuring these crucial air-sea interactions at a global scale. Powered by renewable energy (e.g., wind and waves for propulsion, solar power for electronics), USVs have provided navigable and persistent observing capabilities over the past decade and a half. In our review of 200 USV datasets and 96 studies, we found USVs have observed a total of 33 variables spanning physical, biogeochemical, biological and ecological processes at the air-sea transition zone. We present a map showing the global proliferation of USV adoption for scientific ocean observing. This review, carried out under the auspices of the ‘Observing Air-Sea Interactions Strategy’ (OASIS), makes the case for a permanent USV network to complement the mature and emerging networks within the Global Ocean Observing System (GOOS). The Observations Coordination Group (OCG) overseeing GOOS has identified ten attributes of an in-situ global network. Here, we discuss and evaluate the maturation of the USV network towards meeting these attributes. Our article forms the basis of a roadmap to formalise and guide the global USV community towards a novel and integrated ocean observing frontier.

In order to address the issue of insufficient task offloading decisions in vehicle networks of transportation cyber-physical systems (TCPS) because of multitasking and resource constraints, this study presents a quasi-Newton deep reinforcement learning-based two-stage online offloading (QNRLO) algorithm. Computer simulation experiments show that the approach performs exceptionally well in terms of convergence under various conditions and parameter configurations. Most of the trials are carried out in a simulated setting, and further real-world scenarios may be required to confirm the algorithm's efficacy. This methodology initially implements batch normalization techniques to enhance the training process of the deep neural network, subsequently utilizing the quasi-Newton method for optimization to successfully approximate the ideal answer. According to the experimental results, the QNRLO algorithm's loss function and normalized computation rate have converged after 2,000 iterations, demonstrating the algorithm's excellent stability and dependability. The findings demonstrate). Digital Object Identifier 10.1109/TITS.2025.3539934 that the computational load and training time can be further optimized by appropriately adjusting certain parameters without compromising convergence performance. Furthermore, the technique incorporates system transmission time allocation into the TCPS model, hence augmenting the model's practicality. The proposed approach markedly enhances the efficiency and stability of job offloading compared to previous algorithms, effectively addressing task offloading challenges in TCPS and exhibiting considerable applicability and reliability.

The eco‐friendly processing of conjugated polymer binder for lithium‐ion batteries demands improved polymer solubility by introducing functional moieties, while this strategy will concurrently sacrifice polymer conductivity. Employing the polyfluorene‐based binder poly(2,7‐9,9 (di(oxy‐2,5,8‐trioxadecane))fluorene) (PFO), soluble in water‐ethanol mixtures, a novel approach is presented to solve this trade‐off, which features integration of aqueous solution processing with subsequent controlled thermal‐induced cleavage of solubilizing side chains, to produce hierarchically ordered structures (HOS). The thermal processing can enhance the intermolecular π–π stacking of polyfluorene backbone for better electrochemical performance. Notably, HOS‐PFO demonstrated a substantial 6–7 orders of magnitude enhancement in electronic conductivity, showcasing its potential as a functional binder for lithium‐ion batteries. As an illustration, HOS‐PFO protected SiOx anodes, utilizing in situ side chain decomposition of PFO surrounding SiOx particles after aqueous processing are fabricated. HOS‐PFO contributed to the stable cycling and high‐capacity retention of practical SiOx anodes (3.0 mAh cm⁻²), without the use of any conducting carbon additives or fluorinated electrolyte additives. It is proposed that this technique represents a universal approach for fabricating electrodes with conjugated polymer binders from aqueous solutions without compromising conductivity.

Sleep problems commonly co-occur with serious mental illnesses (SMI) and are associated with negative outcomes, though may be underrecognized and undertreated. This study examined whether clinical services for sleep disorders among Veterans with and without SMI changed during the past decade. The sample included Veterans with a diagnosed sleep disorder in VA VISN 4 (Pennsylvania and sections of Ohio, New Jersey and Delaware) electronic health record data from 2011 to 2019 (N = 77,898). Results revealed that, across 9 years of data, half of Veterans received no sleep services, but among those that did, sleep medications were most common. Notably, Veterans with SMI and sleep disorders were more likely than those without SMI to receive any sleep services, but the proportion of all Veterans receiving sleep services declined across the study period. Results from this study demonstrate that the needs of Veterans with SMI and sleep disorders are met equally well as those of Veterans without SMI, but there remains a large unmet need for all Veterans with sleep disorders, half of whom did not receive any services. Future work should investigate provider and patient perspectives regarding barriers and facilitators to engaging with sleep services, particularly services other than medication.

Due to technological advancement, the advent of smart cities has facilitated the deployment of advanced urban management systems. This integration has been made possible through the Internet of Vehicles (IoV), a foundational technology. By connecting smart cities with vehicles, the IoV enhances the safety and efficiency of transportation. This interconnected system facilitates wireless communication among vehicles, enabling the exchange of crucial traffic information. However, this significant technological advancement also raises concerns regarding privacy for individual users. This paper presents an innovative privacy-preserving authentication scheme focusing on IoV using physical unclonable functions (PUFs). This scheme employs the k-nearest neighbor (KNN) encryption technique, which possesses a multi-multi searching property. The main objective of this scheme is to authenticate autonomous vehicles (AVs) within the IoV framework. An innovative PUF design is applied to generate random keys for our authentication scheme to enhance security. This two-layer security approach protects against various cyber-attacks, including fraudulent identities, man-in-the-middle attacks, and unauthorized access to individual user information. Due to the substantial amount of information that needs to be processed for authentication purposes, our scheme is implemented using hardware acceleration on an Nexys A7-100T FPGA board. Our analysis of privacy and security illustrates the effective accomplishment of specified design goals. Furthermore, the performance analysis reveals that our approach imposes a minimal communication and computational burden and optimally utilizes hardware resources to accomplish design objectives. The results show that the proposed authentication scheme exhibits a non-linear increase in encryption time with a growing AV ID size, starting at 5μs for 100 bits and rising to 39 μs for 800 bits. Also, the result demonstrates a more gradual, linear increase in the search time with a growing AV ID size, starting at less than 1 μs for 100 bits and rising to less than 8 μs for 800 bits. Additionally, for hardware utilization, our scheme uses only 25% from DSP slides and IO pins, 22.2% from BRAM, 5.6% from flip-flops, and 24.3% from LUTs.