LeTourneau University

This work shows that a recursive neural network can be used to provide a categorical prediction of the Center of Gravity (CG) for a unmanned aerial vehicle (UAV) helicopter. A SAB Goblin Raw 420 UAV, with a Pixhawk 6C mini controller was modified to allow for lateral and longitudinal shifts in CG. Flight data from the controller was recorded and used to train a Long Short-Term Memory neural network to estimate and classify the CG location for a given flight. Test results show that the neural network is able to effectively identify the correct CG location.

Work difficulties are a primary issue of multiple sclerosis (MS). This is because disease onset usually occurs during a time when establishing a career and employment is of paramount importance. The MSWDQ-23 (Multiple Sclerosis Work Difficulties Questionnaire) was developed to assess work difficulties in MS. The WORKSEP project aimed to adapt and validate the French MSWDQ-23 and develop cutoff scores through a multicentric study in 14 centers across France. Two hundred and six persons with MS were recruited: 149 with relapsing-remitting MS and 57 with progressive forms of MS. They completed the MSWDQ-23 in French, the DEX to assess the subjective cognitive executive complaint, and the SF-36 evaluating mental (MC) and physical (PC) health-related quality of life. The results indicated that the French version of MSWDQ-23 has high internal consistency (Cronbach's α: 0.93) and test-retest reliability (ICC=0.83). A confirmatory factor analysis demonstrated a scale structure identical to the original English version comprising physical barriers (PB), psychological and cognitive barriers (PCB), and external barriers (EB). The construct and convergent validity were strong. A higher level of work difficulties at PB score was related to a higher level of disability at the EDSS and lower PC quality of life, and a higher level of PCB was related to higher cognitive executive complaints and lower MC quality of life. ROC curves based on the difference between employed and unemployed patients allowed for determining cutoff values of 32 for the total score, 37 for PB, and 27 for PCB. This study allowed the validation of the MSWDQ-23 in the French language and is the first to propose a cutoff. Determining the cutoff value enables identifying patients needing intervention and targets the limitations that MS patients may encounter in the workplace. This easy-to-use instrument provides the opportunity to propose an adapted rehabilitation program or work adjustments to improve the quality of life in patients with MS.

Complete genome sequences of four novel mycobacteriophages, Diminimus, Dulcita, Glaske16, and Koreni, isolated from soil are presented. All these bacteriophages belong to subcluster M1, except Koreni that belongs to subcluster A4. Moreover, all have siphovirus morphologies, with genome sizes ranging from 51,055 to 81,156 bp.

Fluctuating prelicensure educational experiences during the COVID-19 pandemic may result in new nurses entering professional practice without necessary competencies to provide optimal patient care. A virtual clinical practicum was an effective strategy to increase nursing students' confidence across six Quality and Safety Education for Nurses competencies. Importantly, nursing professional development practitioners may utilize this virtual clinical program during onboarding or as part of ongoing career development for nurses across a variety of healthcare systems.

This paper provides an example of discipline-specific biblical faith integration in an Organizational Behavior course through a series of eight faith-integration exercises and a final integrative assignment based on a single book of the Bible, Esther. This approach encourages students to have meaningful dialogue about important biblical concepts as applied to business and management, thus raising their moral and biblical consciences and contributing to their whole-person development. The benefits of this approach are discussed, and the faith-integration assignments and sample responses are included.

Languages morphological context varies by community. The linguistic analysis became more complex due to grammatical variations, cultural, traditional, slang, misspellings, and language variance. Many studies in sentimental analysis have focused on natural language processing and peoples opinions. Text language processing takes time, requires lots of storage space, and a fast computer to work in distributed networks. Many developers choose Hadoop and Map Reduce to process Big Data. This study developed a methodology that employs Apache Spark as a text classification processing engine since it is faster in cluster computing systems. African libraries and packages for language lemmatization and stemming are still lacking. The proposed approach was utilized to detect offensive Swahili texts in social networks. Swahili is the third most widely spoken language in Africa. Four different machine learning techniques were tested as benchmarks, with the multinomial logistic model proving to be the most effective. The evaluation measures show that the proposed machine learning framework is versatile and suitable for usage in centralized and distributed systems.