Texas State University

For the field of academic advising, engaging in professional development can support improvements in daily professional practice in a variety of ways. Participating in professional development (PD) often fosters collaboration and peer-learning within a shared professional environment, building a culture of continuous improvement and strengthening networks. The discourse and research surrounding professional development for academic advisors is mainly centered on how to help advisors connect students to campus resources. We recognize this essential role that academic advisors play in facilitating student-to-campus connections, but we are also interested in how professional development can help advisors grow in their professional field. Thus, this study sought to understand the professional development experiences of academic advisors. Through surveys, focus groups, and individual interviews, we asked academic advisors about their previous PD training, their topic and modality preferences, and the barriers they face in participating in professional development. We found that advisors were very interested in pursuing PD that focused on student success and on their own career goals. However, they often had significant barriers to accessing such professional development. Based on these findings, we advocate for increasing academic advisors’ access to high-quality, individualized professional development opportunities throughout their careers.

Abstract The use of CO 2 exposure in hardened cementitious composites can be employed as a treatment to enhance mechanical performance and capture CO 2 in precast elements. Understanding the role of exposure age on the effectiveness of treatment is crucial to leveraging this approach. This study investigates the influence of CO 2 exposure age on the flexural and microstructural development of cement paste. The samples were divided into two groups. One group was exposed to 24-h accelerated CO 2 exposure on 6-day-old specimens, while the other was exposed to 24-h accelerated CO 2 exposure on 27-day-old specimens. Samples of both groups were tested at 28 days for flexural strength, thermogravimetric analysis (TGA), and quantitative X-ray diffraction (XRD). Besides, additional samples were tested at 7 days. The 28-day flexural strength slightly increased (+ 7%) when the CO 2 exposure was performed at 6 days, while it increased 60% with CO 2 exposure at 27 days, with respect to, in both cases, the 28-day flexural strength of unexposed samples. 7-day XRD and TGA results indicate that the samples exposed at 6 days exhibit lower belite content and lower total hydration products than unexposed samples, suggesting a carbonation of belite and a subsequent reduction in hydration due to the early CO 2 exposure. The 28-day results for TGA and XRD of the samples exposed on the 27th day showed similar CaCO 3 content to the samples exposed on the 6th day, but with more hydration products, purer calcite, and greater crystallinity. Late CO 2 exposure yields greater benefits than early exposure on hydration and carbonate formation, providing better flexural performance.

Image quality assessment (IQA) is a field that focuses on evaluating the quality of images, playing a crucial role in various image processing and/or computer vision applications. Traditional full-reference (FR) IQA algorithms struggle with an accurate perceptual quality evaluation due in part to their reliance on handcrafted features and simple mathematical functions to calculate the elementwise distance between the reference and distorted images. Although deep-learning-based FR IQA methods have shown advantages in providing a certain degree of tolerance to texture resampling, their performances are still limited by the redundant model parameters and ineffective quality-aware feature extraction/representation. To address this issue, in this paper, we propose a multi-modal dual-attention FR IQA algorithm based on combining a global-and-local image structure analysis with text information interpreted by the widely used large language model. Specifically, the proposed multi-modal dual-attention network consists of four modules. First, a global-and-local feature extraction module was employed to extract the quality-aware features from the reference and distorted images, which were then realigned along the spatial and channel dimensions by a feature fusion module. To take into account both the channel and spatial attentions and thus increase the model capacity in representing long-range dependencies among different image areas, a feature enhancement module was designed to encode the spatial information along two directions, based on which the direction-aware attention maps with position information were generated. Finally, the text prior knowledge interpreted by the contrastive language-image pre-training (CLIP) model was embedded to assist the attention-based prediction module for quality estimation. Experimental results on four benchmark datasets demonstrate the effectiveness of our model as compared with other state-of-the-art FR IQA methods. The code is available at https://vinelab.jp/m2da/.

Purpose The purpose of this study is to examine whether differences exist between young American and Japanese consumers' green consumption behaviors. Design/methodology/approach A conceptual framework is formulated based on five constructs: independent self-construal (INDE), attitude toward green advertising, self-expression and brand-familiarity to measure purchase intention. Data were collected from 266 Americans and 199 Japanese consumers. The structural equation model was used to test and compare hypothesized relationships between the proposed constructs for the two countries. Findings The results reveal that the moderating effects of self-construal patterns on brand familiarity and self-expression help explain Americans' green consumption decisions. The results from the US sample also confirm that both self-construal patterns guide young Americans' green consumption behaviors. Japanese green consumption behaviors are influenced by their dominant interdependent self-construal. They used a context-dependent thinking mode to process advertising and brand information. Research limitations/implications Using Gen-Z consumers may limit the generalizability of this study. The results may not be representative of or applicable to other demographic groups. As age was controlled in this research, similar studies need to be replicated with various segments of green consumers to validate the relationships identified in this study. In addition, to raise the external validity of this research, future researchers may replicate this study by comparing countries other than the two under examination in this study. Practical implications For practical implications, marketing communication programs may focus on social interaction strategies by using content or influencer marketing on social media to raise brand awareness. To appeal to Americans' self-expressive values, brand communication may focus on a personalized message that conveys the positive image of green product users. Use both traditional media and digital media to engage with Japanese consumers. To appeal to Japanese collectivist values, the ad message may emphasize the positive effects of the brand and its products on contributing to the well-being of society. Social implications This study detects no evidence of an increase in individualism in Japanese consumers' green consumption behaviors. The results show that consumers' attitudes and behaviors toward green marketing cues are consistently guided by their dominant self-construal patterns and situational factors could activate either self within their self-schema. This also supports the notion that aspects of culture are changeable depending on varying situations. Originality/value This study provides evidence that self-construal types influence young American and Japanese consumers' green consumption behaviors. This is the first research to demonstrate that brand-familiarity can be a group identifier for consumers with different cultural orientations.

Microplastics (MPs), both conventional and biodegradable, are emerging contaminants of significant concern in marine ecosystems. While biodegradable plastics such as polylactic acid (PLA) and polybutylene adipate-co-terephthalate (PBAT) are marketed as eco-friendly alternatives, growing evidence suggests that their degradation products may exhibit comparable toxicity to conventional polymers like polyethylene (PE) and polystyrene (PS). This review critically examines the physicochemical properties, degradation behavior, and ecotoxicological impacts of both biodegradable and conventional MPs on the marine microalga Chlorella vulgaris. The analysis highlights that both MP types inhibit algal growth, disrupt photosynthesis, and induce oxidative stress through reactive oxygen species (ROS) generation, enzymatic imbalance, and cellular membrane damage. Mechanistic pathways involve particle aggregation, surface adsorption, and the release of toxic leachates and nano-sized derivatives, amplifying their ecological risks. Furthermore, biodegradable MPs often fragment faster, increasing MP particle counts and pollutant adsorption potential. The findings challenge the perceived environmental safety of “biodegradable” plastics and underscore the need for realistic field-based assessments. Understanding MP-algae interactions is crucial, as disruptions at this trophic level may cascade through marine food webs, affecting productivity and biogeochemical cycling. The review calls for comprehensive ecotoxicological frameworks to guide sustainable polymer design and effective marine pollution management.

Community development approaches worldwide are frequently designed and implemented without local input, especially in rural areas; top-down, decontextualized strategies and methods lead to outcomes that can be resource inefficient and unsustainable. This case study introduces Demos (Drone-enhanced modeling of scenarios), an innovative methodological approach that aims to articulate local wisdom in pursuit of the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health & Well-Being) and SDG 11 (Sustainable Cities & Communities). Based on open-ended questions, Demos’ first pilot implementation shows promising evidence to convert drone imagery into realistic 3D fly-overs that could unlock a diverse range of participant insights about community development. As a relatively low-cost alternative, Demos enables researchers to deepen participant engagement, enrich qualitative data, and complement traditional techniques. While multiple ethical and logistical hurdles surround the use of drones in social science research, an appropriately designed workflow can be helpful in mitigating these challenges. By repositioning local wisdom to its rightful status as an indispensable source for community development, Demos contributes to strengthening sustainable approaches in similar rural contexts around the globe.