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Noncredit community college programs provide an important route for workforce development. They offer affordable and accessible short-term training options for individuals seeking access to middle-skills jobs. Absent the burdens of accreditation standards, they can respond nimbly to local labor market needs. However, they can also be varied and confusing, and despite the high volume of students that they serve, they are an underexamined area in higher education. This study examines noncredit programs in the New York City labor market to determine how schools align noncredit offerings to the labor market, focusing on credential design, competencies, and market processes. It pursues a push--pull design through a combination of document review and interviews with school leaders and employers and introduces quality taxonomy for understanding employer engagement in individual programs. Implications for students, programs, schools, and employers are explored.

ABSTRACT Aims/Hypothesis In diabetes haptoglobin (Hp) 2 vs Hp 1 allelic product is associated with cardiac and renal complications. Few studies report both Hp phenotype and Hp levels. In a Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial substudy we evaluated the Hp phenotype, Hp levels, and fenofibrate effects. Materials and Methods In 480 adults with type 2 diabetes (T2D) the Hp phenotype was assessed and the Hp level quantified (both using ELISAs assays) in plasma from baseline, after 6 weeks of fenofibrate, and (in n = 200) at 2 years post‐randomization to fenofibrate or placebo. Results The Hp phenotypes 1‐1, 2‐1, and 2‐2 frequencies were 15%, 49%, and 36%, respectively. Baseline Hp levels differed by phenotype (P

Gathering a diverse student body is important for institutions of higher education (IHEs) at the graduate/professional level. However, it is impossible to select a diverse student body from a homogenous group of candidates. Thus the aim of this study is to discover the extent to which diversity goals in admissions are precluded by the lack of diversity in the applicant pool. To explore this, the proportion of score reports sent to the 150 largest graduate/professional schools and sent for each major was compared, from each gender, race, and socioeconomic status (SES) grouping, to proportions from the overall applicant pool of graduate/professional students. Additionally, differences in the distance graduate/professional school applicants are willing to consider traveling by gender, race/ethnicity, and SES were investigated. Results show that differences exist in the gender, race, and SES distributions for score reports sent to different schools and for different majors as well as in the distance an applicant is willing to consider traveling for graduate/professional school. The patterns found for gender, racial, and socioeconomic diversity provide possibilities for researchers to work further together with graduate/professional schools to tackle the important challenge of increasing diversity in graduate/professional education.

Self-comparison (perilaku membandingkan diri) di media sosial cenderung memberikan dampak negatif pada kesehatan mental. Mahasiswa, sebagai pengguna media sosial paling banyak, rentan melakukan perilaku membandingkan diri di media sosial. Self-construal diduga dapat berperan sebagai salah satu prediktor terhadap tingkat social media self-comparison. Tujuan penelitian ini adalah mengkaji apakah independent dan interdependent construal berpengaruh terhadap perilaku membandingkan diri pada mahasiswa. Partisipan dalam penelitian ini sebanyak 485 mahasiswa, berusia 18–25 tahun, dan menggunakan media sosial. Data yang diperoleh dianalisis dengan menggunakan analisis regresi. Hasil dari penelitian ini menunjukkan bahwa hanya interdependent construal yang dapat memprediksi secara signifikan perilaku membandingkan diri di media sosial pada mahasiswa, sedangkan tidak ada korelasi antara independent construal dengan perilaku membandingkan diri di media sosial. Meskipun demikian, interdependent construal hanya berkontribusi sebesar 2% terhadap perilaku membandingkan diri di media sosial. Penelitian ini diharapkan dapat memberikan gambaran bagaimana faktor budaya, khususnya self-construal tertentu dapat mengarah pada munculnya perilaku membandingkan diri di media sosial.

We report a case of a 31-year-old Filipino male with travel history to several European countries in July 2022. He developed five non-tender, well-defined, umbilicated pustules with erythematous borders on the upper lip, left gluteal area, bilateral knees, and left ankle. Skin punch biopsy findings were suggestive of a viral infection. Mpox infection from Clade II (previously known as the West African clade) was confirmed by detecting and amplifying the G2R_G, G2R_WA and C3L gene targets using qPCR. Shotgun metagenomic sequencing subsequently identified a Mpox genome sequence belonging to B.1.3 lineage of Clade IIb, associated with the current multi-country outbreak. Serologic varicella IgM test was positive but varicella PCR of the skin lesion and metagenomic sequencing did not indicate the presence of the varicella virus. The patient was discharged and continued isolation at home until all scabs had completely fallen off. The presence of pustules among patients with risk factors such as possible close physical contact with infected individuals in areas with reported cases of Mpox should raise suspicion for such an infection. Establishment and optimization of qPCR protocol were necessary to confirm Mpox infection. Metagenomic sequencing successfully characterized the etiologic agent of the first laboratory-confirmed Mpox case in the Philippines belonging to Clade IIb which is mainly responsible for the 2022 Mpox global outbreak.

Introduction Diabetes disparities exist based on socioeconomic status, race, and ethnicity. The aim of this study is to compare two cohorts with diabetes from California and Florida to better elucidate how health outcomes are stratified within underserved communities according to state location, race, and ethnicity.Research design and methods Two cohorts were recruited for comparison from 20 Federally Qualified Health Centers as part of a larger ECHO Diabetes program. Participant-level data included surveys and HbA1c collection. Center-level data included Healthcare Effectiveness Data and Information Set metrics. Demographic characteristics were summarized overall and stratified by state (frequencies, percentages, means (95% CIs)). Generalized linear mixed models were used to compute and compare model-estimated rates and means.Results Participant-level cohort: 582 adults with diabetes were recruited (33.0% type 1 diabetes (T1D), 67.0% type 2 diabetes (T2D)). Mean age was 51.1 years (95% CI 49.5, 52.6); 80.7% publicly insured or uninsured; 43.7% non-Hispanic white (NHW), 31.6% Hispanic, 7.9% non-Hispanic black (NHB) and 16.8% other. Center-level cohort: 32 796 adults with diabetes were represented (3.4% with T1D, 96.6% with T2D; 72.7% publicly insured or uninsured). Florida had higher rates of uninsured (p9% HbA1c (p

This community service activity aims to: 1) Provide training on how to produce water hyacinth into various kinds of craft products; 2) Provide training on digital marketing; and 3) Provide training on financial management. The series of training activities took place from August to October 2023. This activity began with an initial coordination meeting to prepare for the implementation of PKM activities with Partners in August 2023, followed by the implementation of training. The partners for this activity are the Sadama Group and the Aua Sarumpun Group with a total of 20 participants. The method used is community development through lectures, discussions, questions and answers, practice and mentoring to provide knowledge and skills in craft making, understanding of digital marketing and financial management. Partners also received assistance from water hyacinth drying machines, press machines and sewing machines. Apart from that, partners also created packaging designs, logo and Instagram designs. The results of this service are important for participants to be able to improve product quality and marketing and financial management of partners.

This study evaluates the Wirid Youth Program implemented at SMAN 2 Lengayang in Pesisir Selatan Regency, aimed at reducing juvenile delinquency and shaping student character. This study adopts a quantitative research paradigm. The evaluation employed the CIPO method (Context, Input, Process, Output) through surveys and interviews with randomly selected participants. The validity of questionnaire items was tested using the Pearson Product Moment formula. The data analysis technique with data collection, data reduction, data presentation, and verification and conclusion drawing. The findings reveal that all program components context, input, process, and output are rated highly. The program effectively addresses teenagers' needs and challenges, provides accessible locations and satisfactory facilities, and is smoothly coordinated. As a result, there is increased teenage participation, enhanced religious knowledge, and positive behavioral changes. The program has met its objectives and positively impacted the participants. This evaluation underscores the program’s success and offers insights for future improvements and program development.

Introduction Obstructive sleep apnoea (OSA) is a common, but underdiagnosed, sleep disorder. If untreated, it leads to poor health outcomes, including Alzheimer’s disease, cancer, cardiovascular disease and all-cause mortality. Our aim is to determine the feasibility and cost-effectiveness of moving the testing for OSA into general practice and how general practitioner (GP)-based screening affects overall detection rates.Methods and analysis Randomised controlled trial of case finding of OSA in general practice using a novel Medicines and Healthcare products Regulatory Agency-registered device (AcuPebble SA100) compared with usual care with internal feasibility phase. A diverse sample of general practices (approximately 40) from across the West Midlands Clinical Research Network will identify participants from their records. Eligible participants will be aged 50–70 years with body mass index >30 kg/m2 and diabetes (type 1 or 2) and/or hypertension (office blood pressure >145/90 mm Hg or on treatment). They will exclude individuals with known OSA or chronic obstructive pulmonary disease, or those they deem unable to take part. After eligibility screening, consent and baseline assessment, participants will be randomised to either the intervention or control group. Participants in the intervention arm will receive by post the AcuPebble sleep test kit. Those in the control arm will continue with usual care. Follow-up questionnaires will be completed at 6 months. The study is powered (90%) to detect a 5% difference and will require 606 patients in each arm (713 will be recruited to each arm to allow for attrition). Due to the nature of the intervention, participants and GPs will not be blinded to the allocation.Outcomes Primary: Detection rate of moderate-to-severe OSA in the intervention group versus control group. Secondary: Time to diagnosis and time to treatment for intervention versus control group for mild, moderate and severe OSA; cost-effectiveness analysis comparing the different testing pathways.Ethics and dissemination The trial started on 1 November 2022. Ethical approval was granted from the South Central Oxford A Research Ethics Committee on 9 June 2023 (23/SC/0188) (protocol amendment version 1.3; update with amendment and approval to renumber to V2.0 on 29 August 2023). Patient recruitment began on 7 January 2024; initial planned end date will be on 31 April 2025.Results will be uploaded to the ISRCTN register within 12 months of the end of the trial date, presented at conferences, submitted to peer-reviewed journals and distributed via our patient and public involvement networks.The University of Warwick will act as the trial sponsor. The trial will be conducted in accordance with the Sponsor and Primary Care Clinical Trials Unit standard operating procedures.Trial registration number ISRCTN 16982033.

Facing the challenges of globalization and technological advancements, developing entrepreneurial character is vital in shaping innovative, proactive, socially and ethically responsible individuals. This study aims to analyze the implementation of entrepreneurial character education through the independent curriculum and the Rahmatan Lil Alamin profile in students of state Islamic high schools to develop character and ethical values that support professional success and positive contributions to society. To create young entrepreneurs with responsible and faithful character, education in schools plays and essential role in forming entrepreneurial character. This research is a qualitative descriptive study, with the subjects being one principal and 29 teachers at State Madrasah Aliyah Insan Cendekia Padang Pariaman. The data used consisted of primary data (observations and interviews) and secondary data (information from literature studies). The data analysis process underwent the stages of collection, processing, and presentation of results. This study reveals that State Madrasah Aliyah Insan Cendekia Padang Pariaman has successfully implemented entrepreneurial character education by integrating entrepreneurial values into the curriculum, supported by experiential learning approaches and social interactions. Therefore, the conclusion showed that the Rahmatal Lil Alamin Curriculum was sufficiently implemented at MAN Insan Cendekia Padang Pariama.

In today’s rapidly evolving labor market, the emergence of new roles and the decline of traditional ones have led to a complex landscape of job titles and skill requirements. This complexity often causes ambiguity and confusion, affecting both novices and experienced professionals. To address this, extensive international efforts have produced reference databases of jobs and skills, such as ESCO and O*NET. However, the challenge remains to make this information easily accessible and interpretable for users with varying levels of expertise. To address the challenge above, this paper introduces a Knowledge Plug-in for ChatGPT, designed to serve as an intuitive, user-friendly interface between workers and these authoritative databases. By harnessing the power of natural language processing (NLP), the plug-in enables a seamless question-answering experience, effectively masking the underlying complexity with a carefully engineered architecture. Furthermore, generative AI enhances the user experience by providing relevant information in domains extending beyond the traditional scope of employment. An initial user study demonstrates the plug-in’s effectiveness in improving the usability and accuracy of job-related queries. We detail the development, architecture, and validation of this innovative tool, highlighting its potential impact on the future of employment search and career development.

The labor market is a dynamic and rapidly evolving environment. Job positions that require expertise in various sectors often lead candidates to question their suitability. Therefore, it is crucial to furnish them with relevant, accurate, and timely information. In this article, we introduce a knowledge plug-in for existing conversational agents designed to address specific queries related to the job market domain. Additionally, we propose an innovative method for dynamically creating diverse grammars and semantically associating users’ questions with a predefined list of domain questions. We present a novel scheme to effectively tackle question-answering tasks in settings with limited resources. Our architecture relies on question-understanding and response-generation modules, both powered by Transformers, the O*NET occupational database, and recommendation engines that suggest training materials. Furthermore, we conducted a user study based on the System Usability Scale (SUS) score, revealing that users highly appreciated the proposed tool. This sentiment was particularly evident when the tool was integrated with other artificial intelligence chatbots capable of handling general information. Simultaneously, our engine adeptly manages information within the investigated domain, providing precise responses and recommendations. This work addresses a critical gap in the delivery of employment information and paves the way for the development of diverse functionalities to assist both candidates and employers.

In recent years, the significance of Environmental, Social, and Governance criteria in assessing financial investments has grown significantly. This paper presents an AI-driven analysis of ESG concepts and their evolution from 1980 to 2022, with a specific focus on media sources from the United States and the United Kingdom. The primary data source utilized is the Dow Jones News Article dataset, providing a comprehensive and high-quality collection of news articles. The study introduces a novel technique for information extraction from news articles, involving the structuring of extracted data into a knowledge graph. The findings identified key trends associated with ESG aspects emerging in recent years. In the environmental dimension, we identified pronounced emphasis on climate change, renewable energy sources, and biodiversity conservation. Within the social aspect, the analysis pointed out the increasing significance of issues such as racism, gender identity, human rights as well all the increasing role of charities, and the ethical challenges of modern supply chains. Finally, in the governance domain, the findings emphasized issues related to corporate governance accountability, workplace ethics, and the conduct and remuneration of executives.

According to Sanad, the pronunciation of Hijaiyah letters can serve as a benchmark for correct or valid reading based on the makhraj and properties of the letters. However, the limited number of Qur'anic Sanad teachers remains one of the obstacles to learning the Qur'an. This study aims to identify the most practical combination of classification models in constructing a voice recognition system that facilitates learning without requiring direct interaction with a teacher. The methods employed include the XGBoost algorithm and CNN. As a result, out of the 12 letter trait labels, the CNN model was utilized for 10 of them, specifically for traits S1, S2, S4, S5, T1, T2, T3, T4, T5, and T6, on trait labels S3 and T7 applying the XGBoost model. Furthermore, the inclusion of additional data yielded performance results for each property, with an average accuracy of 78.14% for property S (letters with opposing properties), 70.69% for property T (letters without opposing properties), and an overall average of 73.79% per letter.