A Bayesian Survival Analysis on Long COVID and non Long COVID patients: A Cohort Study Using National COVID Cohort Collaborative (N3C) Data.

Since the outbreak of COVID-19 pandemic in 2020, numerous researches and studies have focused on the long-term effects of COVID infection. The Centers for Disease Control (CDC) implemented an additional code into the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) for reporting 'Post COVID-19 condition, unspecified (U09.9)' effective on October 1st 2021, representing that Long COVID is a real illness with potential chronic conditions. The National COVID Cohort Collaborative (N3C) provides researchers with abundant electronic health records (EHR) data by aggregating and harmonizing EHR data across different clinical organizations in the United States, making it convenient to build up a survival analysis on Long COVID patients and non Long COVID patients among large amounts of COVID positive patients.

Exploring the impact of stage and tumor site on colorectal cancer survival: Bayesian survival modeling.

Colorectal cancer is a prevalent malignancy with global significance. This retrospective study aimed to investigate the influence of stage and tumor site on survival outcomes in 284 colorectal cancer patients diagnosed between 2001 and 2017. Patients were categorized into four groups based on tumor site (colon and rectum) and disease stage (early stage and advanced stage). Demographic characteristics, treatment modalities, and survival outcomes were recorded. Bayesian survival modeling was performed using semi-competing risks illness-death models with an accelerated failure time (AFT) approach, utilizing R 4.1 software. Results demonstrated significantly higher time ratios for disease recurrence (TR = 1.712, 95% CI 1.489-2.197), mortality without recurrence (TR = 1.933, 1.480-2.510), and mortality after recurrence (TR = 1.847, 1.147-2.178) in early-stage colon cancer compared to early-stage rectal cancer. Furthermore, patients with advanced-stage rectal cancer exhibited shorter survival times for disease recurrence than patients with early-stage colon cancer. The interaction effect between the disease site and cancer stage was not significant. These findings, derived from the optimal Bayesian log-normal model for terminal and non-terminal events, highlight the importance of early detection and effective management strategies for colon cancer. Early-stage colon cancer demonstrated improved survival rates for disease recurrence, mortality without recurrence, and mortality after recurrence compared to other stages. Early intervention and comprehensive care are crucial to enhance prognosis and minimize adverse events in colon cancer patients.

Is the performance at the implicit association test sensitive to feedback presentation? A Rasch-based analysis.

The Implicit Association Test (IAT) is commonly used for the indirect assessment of psychological constructs. While the features of the IAT that might influence the performance of the respondents have been extensively investigated, the effect of informing the respondents about the correctness of their responses (i.e., feedback presentation) has been poorly addressed so far. The study addresses this issue by presenting an across-domain (implicit prejudice and food preference) Rasch-based analysis of IAT data obtained with and without feedback presentation. Results showed that speed was influenced by the interaction between feedback presentation and associative condition, whereas accuracy was influenced by the associative condition. This result varied across-domain. Results suggested that IATs administered with feedback presentation provide more accurate information on the construct of interest.

Application of Change Point Analysis of Response Time Data to Detect Test Speededness.

Computer-based and web-based testing have become increasingly popular in recent years. Their popularity has dramatically expanded the availability of response time data. Compared to the conventional item response data that are often dichotomous or polytomous, response time has the advantage of being continuous and can be collected in an unobstrusive manner. It therefore has great potential to improve many measurement activities. In this paper, we propose a change point analysis (CPA) procedure to detect test speededness using response time data. Specifically, two test statistics based on CPA, the likelihood ratio test and Wald test, are proposed to detect test speededness. A simulation study has been conducted to evaluate the performance of the proposed CPA procedure, as well as the use of asymptotic and empirical critical values. Results indicate that the proposed procedure leads to high power in detecting test speededness, while keeping the false positive rate under control, even when simplistic and liberal critical values are used. Accuracy of the estimation of the actual change point, however, is highly dependent on the true change point. A real data example is also provided to illustrate the utility of the proposed procedure and its contrast to the response-only procedure. Implications of the findings are discussed at the end.

Fingerprint detection and using intercalated CdSe nanoparticles on non-porous surfaces.

A fluorescent nanocomposite based on the inclusion of CdSe quantum dots in porous phosphate heterostructures, functionalized with amino groups (PPH-NH2@CdSe), was synthesized, characterized and used for fingerprint detection. The main scopes of this work were first to develop a friendly chemical powder for detecting latent fingerprints, especially in non-porous surfaces; their further intercalation in PPH structure enables not to spread the fluorescent nanoparticles, for that reason very good fluorescent images can be obtained. The fingerprints, obtained on different non-porous surfaces such as iron tweezers, mobile telephone screen and magnetic band of a credit card, treated with this powder emit a pale orange luminescence under ultraviolet excitation. A further image processing consists of contrast enhancement that allows obtaining positive matches according to the information supplied from a police database, and showed to be more effective than that obtained with the non-processed images. Experimental results illustrate the effectiveness of proposed methods.