[{"id":8540,"date":"2026-04-01T16:36:10","date_gmt":"2026-04-01T21:36:10","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8540"},"modified":"2026-04-01T16:37:57","modified_gmt":"2026-04-01T21:37:57","slug":"identity-leadership-with-mr-stedman-graham","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/identity-leadership-with-mr-stedman-graham\/","title":{"rendered":"Identity Leadership with Mr. Stedman Graham"},"content":{"rendered":"
Tuesday, Apr 7, 11:00 am<\/div>\n
\n

Mr<\/span>. Graham<\/span> will be presenting on Identity Leadership on April 7th at 11:00 am in the Don Clark (Juvenile Justice) Auditorium. This event is a collaborative effort led by Student Affairs, in partnership with the Development Office, the Graduate School, and the President’s Office.<\/p>\n

\n<\/div>\n

\n
Event Link<\/div>\n

https:\/\/www.pvamu.edu\/event\/identity-leadership-with-mr-stedman-graham\/<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Tuesday, Apr 7, 11:00 am Mr. Graham will be presenting on Identity Leadership on April 7th at 11:00 am in the Don Clark (Juvenile Justice) Auditorium. This event is a collaborative effort led by Student Affairs, in partnership with the Development Office, the Graduate School, and the President’s Office. Event Link https:\/\/www.pvamu.edu\/event\/identity-leadership-with-mr-stedman-graham\/<\/p>\n","protected":false},"author":432,"featured_media":8541,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[382,136],"class_list":["post-8540","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8540","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8540"}],"version-history":[{"count":2,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8540\/revisions"}],"predecessor-version":[{"id":8543,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8540\/revisions\/8543"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/8541"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8540"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8540"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8540"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8540"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8535,"date":"2026-04-01T10:36:36","date_gmt":"2026-04-01T15:36:36","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8535"},"modified":"2026-04-01T10:38:24","modified_gmt":"2026-04-01T15:38:24","slug":"md-symum-islam-masters-thesis-defense-thursday-april-9-2026-1230-pm-central-time","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/md-symum-islam-masters-thesis-defense-thursday-april-9-2026-1230-pm-central-time\/","title":{"rendered":"MD Symum Islam Master\u2019s Thesis Defense, Thursday, April 9, 2026 @ 12:30 pm Central Time"},"content":{"rendered":"

COMMITTEE CHAIR<\/strong>: Dr. Ali Fares
\nCO-COMMITTEE CHAIR<\/strong>: Dr. Ripendra Awal<\/p>\n

TITLE<\/strong>: ASSESSING THE FUTURE IMPACTS OF DROUGHT ON COTTON YIELD IN TEXAS USING MACHINE LEARNING AND CLIMATE INDICES<\/p>\n

ABSTRACT: <\/strong>Climate change and increasing drought frequency pose significant challenges to agricultural sustainability in Texas. It particularly impacts cotton production, which is highly sensitive to temperature variability and water availability. Despite numerous studies evaluating climate impacts on agriculture, limited research integrates climate projections to predict cotton yield. There is also few research on drought indices, machine learning models, and crop simulation models to assess future cotton yield vulnerability across Texas climate divisions. Therefore, this study evaluates historical climate trends, compares predictive modeling approaches, and projects future cotton yield under climate change scenarios. Historical climate variables including maximum temperature (Tmax), minimum temperature (Tmin), precipitation (PR), potential evapotranspiration (PET), soil water storage (STOR), and drought indices (SPI-3, SPI-6, SPEI-3, and SPEI-6) were analyzed with cotton yield data from 1968 \u2013 2024. Multiple Linear Regression (MLR) and Random Forest (RF) models were developed and evaluated using correlation coefficient (R) and Root Mean Square Error (RMSE). Future climate projections from CMIP6 LOCA datasets under SSP245 and SSP585 scenarios were used to project cotton yield for 2030\u20132050. Additionally, the FAO AquaCrop model was used to simulate crop response to water availability and validate machine learning projections. Results indicate that temperature and PET were the most influential predictors of cotton yield across Texas climate divisions. RF models showed improved predictive performance with R values ranging from approximately 0.62 to 0.89, compared to MLR values ranging from 0.48 to 0.81. AquaCrop validation showed low to moderate correlation with observed yields (R \u02dc -0.05 to 0.48). Future projections indicate yield increases of approximately 9\u201321% in North Central and High Plains divisions, while declines of approximately 6\u201311% are projected in South Central and Upper Coast regions. Irrigated cotton showed greater resilience compared to non-irrigated systems. Overall, this study demonstrates that integrating machine learning and crop simulation models improves climate impact assessment and supports climate-resilient agricultural management strategies in Texas.<\/p>\n

Keywords: <\/strong>Cotton yield, machine learning, drought indices (Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI)), AquaCrop model, Random<\/p>\n","protected":false},"excerpt":{"rendered":"

COMMITTEE CHAIR: Dr. Ali Fares CO-COMMITTEE CHAIR: Dr. Ripendra Awal TITLE: ASSESSING THE FUTURE IMPACTS OF DROUGHT ON COTTON YIELD IN TEXAS USING MACHINE LEARNING AND CLIMATE INDICES ABSTRACT: Climate change and increasing drought frequency pose significant challenges to agricultural sustainability in Texas. It particularly impacts cotton production, which is highly sensitive to temperature variability […]<\/p>\n","protected":false},"author":432,"featured_media":7636,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[],"class_list":["post-8535","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8535","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8535"}],"version-history":[{"count":1,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8535\/revisions"}],"predecessor-version":[{"id":8537,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8535\/revisions\/8537"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/7636"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8535"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8535"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8535"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8535"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8521,"date":"2026-03-31T13:23:35","date_gmt":"2026-03-31T18:23:35","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8521"},"modified":"2026-03-31T14:20:55","modified_gmt":"2026-03-31T19:20:55","slug":"hussein-rajabu-masters-thesis-defense-friday-april-17-2026-230-pm-central-time","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/hussein-rajabu-masters-thesis-defense-friday-april-17-2026-230-pm-central-time\/","title":{"rendered":"Hussein Rajabu Master\u2019s Thesis Defense, Friday, April 17, 2026 @ 2:30 pm Central Time"},"content":{"rendered":"

COMMITTEE CHAIR<\/strong>: Dr. Xishuang Dong<\/p>\n

TITLE<\/strong>: MULTI-TASK GROWING INTERPRETABLE NEURAL NETWORK FOR MULTI-TARGET SYMBOLIC REGRESSION<\/p>\n

ABSTRACT: <\/strong>Over the past decade, deep learning has achieved remarkable success across a wide range of domains, including computer vision and natural language processing. Despite their strong performance, these models often operate as black boxes, making it difficult to understand how decisions are made. This lack of transparency poses significant challenges for deploying deep learning techniques in high-stakes applications such as healthcare and business analytics, where interpretability is essential. To address this issue, explainable artificial intelligence (XAI) and interpretable AI techniques have been developed to provide insights into model behavior. However, most existing approaches primarily capture statistical associations between inputs and outputs rather than uncovering the underlying functional mechanisms driving predictions. Symbolic regression (SR) has recently gained attention as a promising approach within interpretable AI. Unlike traditional methods, SR aims to discover explicit mathematical expressions that describe the relationships between variables, offering both interpretability and competitive predictive performance. Although SR has advanced significantly in recent years, two major challenges remain. First, SR methods are primarily developed and validated on scientific datasets, such as those from physics and chemistry, where underlying relationships are relatively well understood. This limits their applicability to broader, data-driven machine learning tasks. Second, most SR approaches focus on single-target regression, while many real-world problems involve multiple correlated outputs that share common information. To address these limitations, this thesis proposes Multi-Task Regression GINN-LP (MTRGINN-LP), a novel neuro-symbolic framework for multi-target symbolic regression. Building upon GINN-LP, the model introduces Power-Term Approximator Blocks to effectively capture power-law relationships in data. It further integrates multi-task learning through a shared backbone combined with task-specific output layers, enabling the discovery of shared symbolic representations while maintaining task-level interpretability. Additionally, a symbolic loss function is introduced to align symbolic predictions with regression outputs during training. The proposed method is evaluated on diverse multi-target regression tasks, including energy efficiency analysis and sustainable agriculture. Experimental results demonstrate that the approach achieves competitive predictive performance while preserving strong interpretability, effectively bridging the gap between symbolic regression and practical multi-output learning scenarios.<\/p>\n

Keywords: <\/strong>Interpretable AI, Multi-task Learning, Multi-target Regression, Symbolic AI<\/p>\n

Room Location: <\/strong>Electrical Engineering Conference Room 315D<\/p>\n","protected":false},"excerpt":{"rendered":"

COMMITTEE CHAIR: Dr. Xishuang Dong TITLE: MULTI-TASK GROWING INTERPRETABLE NEURAL NETWORK FOR MULTI-TARGET SYMBOLIC REGRESSION ABSTRACT: Over the past decade, deep learning has achieved remarkable success across a wide range of domains, including computer vision and natural language processing. Despite their strong performance, these models often operate as black boxes, making it difficult to understand […]<\/p>\n","protected":false},"author":432,"featured_media":7636,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[],"class_list":["post-8521","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8521","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8521"}],"version-history":[{"count":3,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8521\/revisions"}],"predecessor-version":[{"id":8530,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8521\/revisions\/8530"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/7636"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8521"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8521"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8521"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8521"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8519,"date":"2026-03-31T13:15:00","date_gmt":"2026-03-31T18:15:00","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8519"},"modified":"2026-03-31T14:15:49","modified_gmt":"2026-03-31T19:15:49","slug":"temitayo-ogunsusi-masters-thesis-defense-friday-april-17-2026-1100-am-central-time","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/temitayo-ogunsusi-masters-thesis-defense-friday-april-17-2026-1100-am-central-time\/","title":{"rendered":"Temitayo Ogunsusi Master\u2019s Thesis Defense, Friday, April 17, 2026 @ 11:00 am Central Time"},"content":{"rendered":"

COMMITTEE CHAIR<\/strong>: Dr. Xishuang Dong<\/p>\n

TITLE<\/strong>: LLMS-BASED TEXT-TO-SQL FOR GEOSPATIAL INFORMATION RETRIEVAL<\/p>\n

ABSTRACT: <\/strong>Text-to-SQL aims to translate natural language questions into SQL queries that can be executed on databases, enabling non-expert users to retrieve information without learning formal query languages. Early Text-to-SQL systems relied on rule-based methods and semantic parsers, while recent advances in deep learning have achieved strong performance by jointly encoding user questions and database schemas. However, these approaches typically require large annotated datasets and specific model architectures. With the emergence of large language models (LLMs), such as GPT-4, Llama, and Gemma, Text-to-SQL systems can leverage powerful natural language understanding capabilities to generate SQL queries using zero-shot or few-shot prompting. Despite these advancements, existing research has largely focused on conventional relational databases, with limited attention given to geospatial databases that involve specialized spatial data types and functions. This thesis addresses this gap by investigating LLM-based Text-to-SQL for geospatial information retrieval. We construct a new benchmark dataset with a PostGIS spatial database, containing natural language questions paired with SQL queries that incorporate spatial operations such as distance calculations, spatial joins, and geometric predicates. To expand the dataset and improve diversity, additional question-query pairs are generated through LLM-based data augmentation. Furthermore, building on this benchmark, we develop a Text-to-SQL pipeline that integrates multiple state-of-the-art LLMs to translate natural language queries into executable spatial SQL statements. The system incorporates database schema information within prompts to improve query generation. Experimental results demonstrate that the proposed pipeline can effectively retrieve geospatial information using natural language queries, achieving competitive performance regarding Execution Accuracy and Valid Efficiency Score.<\/p>\n

Keywords: <\/strong>Text-to-SQL, Large Language Models, Information Retrieval, Geospatial Database<\/p>\n

Room Location: <\/strong>Electrical Engineering Conference Room 315D<\/p>\n","protected":false},"excerpt":{"rendered":"

COMMITTEE CHAIR: Dr. Xishuang Dong TITLE: LLMS-BASED TEXT-TO-SQL FOR GEOSPATIAL INFORMATION RETRIEVAL ABSTRACT: Text-to-SQL aims to translate natural language questions into SQL queries that can be executed on databases, enabling non-expert users to retrieve information without learning formal query languages. Early Text-to-SQL systems relied on rule-based methods and semantic parsers, while recent advances in deep […]<\/p>\n","protected":false},"author":432,"featured_media":7636,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[535],"class_list":["post-8519","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8519","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8519"}],"version-history":[{"count":3,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8519\/revisions"}],"predecessor-version":[{"id":8526,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8519\/revisions\/8526"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/7636"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8519"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8519"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8519"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8519"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8517,"date":"2026-03-31T13:11:00","date_gmt":"2026-03-31T18:11:00","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8517"},"modified":"2026-03-31T13:12:57","modified_gmt":"2026-03-31T18:12:57","slug":"carl-daniel-doctoral-project-defense-monday-april-13-2026-300-pm-central-time","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/carl-daniel-doctoral-project-defense-monday-april-13-2026-300-pm-central-time\/","title":{"rendered":"Carl Daniel Doctoral Project Defense, Monday, April 13, 2026 @ 3:00 pm Central Time"},"content":{"rendered":"

COMMITTEE CHAIR<\/strong>: Dr. Sharisse Hebert<\/p>\n

TITLE<\/strong>: IMPROVING HOT DEBRIEF COMPLETION RATES AFTER RAPID RESPONSE TEAM EVENTS THROUGH QR CODE ACCESS AND DIGITAL REMINDERS: A QUALITY IMPROVEMENT PROJECT<\/p>\n

ABSTRACT: <\/strong>Rapid Response Teams (RRTs) are critical for stabilizing acutely deteriorating patients. However, structured hot debriefs, which are brief reflections held immediately after emergencies, are inconsistently documented, despite benefits for communication, safety, and staff well-being. At a large academic hospital in Southeast Texas, only 35.76% of RRT events in 2025 included completed hot debrief forms. A January 2025 hospital-led survey of Clinical Emergency Response Team (CERT) Advanced Practice Registered Nurses (APRNs) identified barriers such as time constraints, limited access, and forgetfulness. Purpose: This Doctor of Nursing Practice (DNP) quality improvement project (QI) evaluated whether a bundled intervention, QR code access to forms, twice daily SMS reminders (9:00 a.m. and 9:00 p.m.), and brief education, increases hot debrief documentation rates after RRT events. Methods: Guided by the Plan-Do-Check-Act (PDCA) framework, this pre- and post-intervention design was implemented at a large academic hospital in Southeast Texas. The project involved 40 CERT APRNs conducting adult inpatient debriefs across about 729 RRT events in three months. Microsoft Forms was used for secure data collection, and pre-\/post-surveys assessed perceived barriers and attitudes. Intervention activities included QR code distribution, scheduled twice-daily SMS reminders (9:00 a.m. and 9:00 p.m.), and structured debriefing education. Descriptive statistics and chi-square tests compared pre- and post-intervention documentation rates. The approach offered a scalable, cost-effective strategy to enhance communication, support staff recovery, and strengthen safety learning.<\/p>\n

Keywords<\/strong>: Hot Debrief, Rapid Response Team, QR Code, Digital Reminder, Advanced Practice Registered Nurse, Quality Improvement, Emergency Response, Documentation Compliance, PDCA Cycle<\/p>\n

Location Online:<\/strong><\/p>\n

Zoom Link<\/strong>: https:\/\/pvpanther.zoom.us\/j\/96912933947?pwd=7JtIHymgoSbo0fIJCofRaQJAiTVN4N.1<\/a><\/p>\n

Meeting ID<\/strong>: 933 2678 4995<\/p>\n

Passcode<\/strong>: 467899<\/p>\n","protected":false},"excerpt":{"rendered":"

COMMITTEE CHAIR: Dr. Sharisse Hebert TITLE: IMPROVING HOT DEBRIEF COMPLETION RATES AFTER RAPID RESPONSE TEAM EVENTS THROUGH QR CODE ACCESS AND DIGITAL REMINDERS: A QUALITY IMPROVEMENT PROJECT ABSTRACT: Rapid Response Teams (RRTs) are critical for stabilizing acutely deteriorating patients. However, structured hot debriefs, which are brief reflections held immediately after emergencies, are inconsistently documented, despite […]<\/p>\n","protected":false},"author":432,"featured_media":7636,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[],"class_list":["post-8517","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8517","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8517"}],"version-history":[{"count":1,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8517\/revisions"}],"predecessor-version":[{"id":8518,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8517\/revisions\/8518"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/7636"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8517"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8517"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8517"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8517"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8513,"date":"2026-03-25T14:38:51","date_gmt":"2026-03-25T19:38:51","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8513"},"modified":"2026-03-25T14:39:01","modified_gmt":"2026-03-25T19:39:01","slug":"pvamu-2026-2027-general-scholarship-application-has-been-extended","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/pvamu-2026-2027-general-scholarship-application-has-been-extended\/","title":{"rendered":"PVAMU 2026\u20132027 General Scholarship Application has been EXTENDED"},"content":{"rendered":"

\n

Guess what, Panthers! <\/span>🐾<\/p>\n<\/div>\n

\n

The deadline for the PVAMU 2026\u20132027 General Scholarship Application has been EXTENDED to May 15th<\/strong>! 🎉<\/p>\n<\/div>\n

\n

There\u2019s still time to secure funding for your future. Don\u2019t miss this opportunity.<\/p>\n<\/div>\n

\n

🔗Apply today: https:\/\/pvamu.academicworks.com\/<\/a><\/p>\n<\/div>\n

\n

<\/a>Best regards,<\/p>\n

 <\/p>\n

\n
\n

\"This<\/a><\/p>\n<\/div>\n<\/div>\n

Default Prevention – Financial Aid<\/a><\/p>\n

\u00a0<\/i><\/b><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Guess what, Panthers! 🐾 The deadline for the PVAMU 2026\u20132027 General Scholarship Application has been EXTENDED to May 15th! 🎉 There\u2019s still time to secure funding for your future. Don\u2019t miss this opportunity. 🔗Apply today: https:\/\/pvamu.academicworks.com\/ Best regards,   Default Prevention – Financial Aid \u00a0<\/p>\n","protected":false},"author":432,"featured_media":8514,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[],"class_list":["post-8513","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8513","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8513"}],"version-history":[{"count":1,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8513\/revisions"}],"predecessor-version":[{"id":8515,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8513\/revisions\/8515"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/8514"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8513"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8513"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8513"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8513"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8100,"date":"2025-12-15T10:02:28","date_gmt":"2025-12-15T16:02:28","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8100"},"modified":"2025-12-15T13:00:45","modified_gmt":"2025-12-15T19:00:45","slug":"commencement-for-doctoral-and-masters-candidates-only-2","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/commencement-for-doctoral-and-masters-candidates-only-2\/","title":{"rendered":"COMMENCEMENT 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