Background: In addition to newborn screening, dried blood spots (DBSs) are used for a wide variety of analytes for clinical, epidemiological, and research purposes. Guidelines on DBS collection, storage, and transport are available, but it is suggested that each laboratory should establish its own acceptance criteria. Methods: An optical scanning device was developed to assess the quality of DBSs received in the newborn screening laboratory from 11 maternity wards between 2013 and 2018. The algorithm was adjusted to agree with the visual examination consensus of experienced laboratory personnel. Once validated, the algorithm was used to categorize DBS specimens as either proper or improper. Improper DBS specimens were further divided based on 4 types of specimen defects. Results: In total, 27 301 DBSs were analyzed. Compared with an annual DBS rejection rate of about 1%, automated scanning rejected 26.96% of the specimens as having at least one defect. The most common specimen defect was multi-spotting (ragged DBS, 19.13%). Among maternity wards, improper specimen rates varied greatly between 5.70% and 49.92%. Conclusions: Improper specimen rates, as well as the dominant type of defect(s), are mainly institution-dependent, with various maternity wards consistently showing specific patterns of both parameters over time. Although validated in agreement with experienced laboratory personnel consensus, automated analysis rejects significantly more specimens. While continuous staff training, specimen quality monitoring, and problem-reporting to maternities is recommended, a thorough quality assessment strategy should also be implemented by every newborn screening laboratory. An important role in this regard may be played by automation in the form of optical scanning devices.

Biomedical Engineering programs are present at many universities all over the world with an increasing trend. New generations of biomedical engineers have to face the challenges of health care systems round the world which need a large number of professionals not only to support the present technology in the health care system but to develop new devices and services. Biomedical Engineering supports patient diagnosis and treatment by installing, testing, calibrating and repairing biomedical equipment; training users; maintaining safe operations. Also, approves new equipment by conducting tests, ensuring adherence to codes and making modifications. This paper presents a solution for biomedical signal processing education, involving real signal acquisition and computer-based processing. The acquired signals also allow a lot of post processing procedures to be implemented in an educational form/way.

In proficiency testing (PT), a consensus assigned value is an estimate whose uncertainty can affect participants’ performance classifications. This study evaluated the relationship between formula-based assigned-value uncertainty, empirical sampling variability and classification discordance under limited participation. Using gravimetric calibration of a 100 µL micropipette, 147.2 million Monte Carlo PT rounds were simulated across 1472 scenarios combining participant numbers (N = 5–50), two dispersion levels referenced to ISO 8655-2:2022 and outlier contamination (0–30%). The arithmetic mean and ISO 13528 Algorithm A were compared regarding assigned-value variability, uncertainty calibration, stability and classification. The 95th percentile of the assigned-value uncertainty ratio frequently exceeded the ISO 13528 threshold of 0.3, particularly under contamination and limited participation. This ratio was strongly associated with scenario-level decisional discordance (Spearman ρ = 0.97–0.99). Formula-based uncertainty exceeded empirical Monte Carlo variability for Algorithm A in all 1472 scenarios (calibration ratios of 1.044–1.301), whereas the arithmetic mean’s ratios ranged from 0.856 to 0.998. Although Algorithm A generally improved empirical stability under contamination, this advantage did not consistently translate into lower participant-number requirements under the combined acceptance criterion. These findings demonstrate that estimator robustness and uncertainty-formula calibration are distinct properties requiring separate evaluation when designing PT schemes with limited participation.

Background/Objectives: Private dental markets operating under fee-for-service arrangements lack the structural accountability mechanisms that typically drive quality governance adoption in publicly funded systems. In Romania, where no private dental office currently holds formal accreditation, accreditation-seeking reflects a genuine behavioral choice rather than a regulatory compliance. This study examined whether financing structure and Professional Governance behavior operate as distinct determinants of accreditation-seeking intention among private dental practitioners and which pathway offers a more tractable entry point for quality policy intervention. Methods: A cross-sectional survey was conducted among 98 licensed private dental practitioners in Romania (November 2025–January 2026). Three domain composites were derived from a 31-item de novo instrument anchored in JCI, ANMCS, and EN ISO 9001:2015 standards: Professional Governance, Patient Rights and Ethics, and Patient Safety Behaviors. The financing profile was operationalized as engagement with the national public insurance system (CNAS). Binary logistic regression modeled high accreditation-seeking intention (Q31 ≥ 4) against standardized domain scores and financing engagement, with bootstrap confidence intervals from 2000 replicates. Results: Two predictors independently and significantly predicted high accreditation-seeking intention. CNAS engagement showed the strongest association (OR = 5.05, 95% bootstrap CI [1.87–17.91], and p = 0.003), while the Professional Governance score remained independently associated (OR = 2.68, 95% bootstrap CI [1.63–5.63], and p = 0.003). The Patient Rights and Ethics score was not significant. Practitioners actively exploring CNAS contracting showed the highest accreditation-seeking intention (exceeding that of established contractors), suggesting a possible transitional accountability dynamic during financing transition, though this interpretation requires prospective longitudinal validation. Model performance was good (AUC = 0.788; Nagelkerke R² = 0.339). Conclusions: Both financing engagement and governance behavior predicted accreditation-seeking intention after mutual adjustment, representing distinct pathways to voluntary quality adoption in private dental practice. Policy interventions aligned with entry into public contracting and with practice-level governance development are more likely to support accreditation uptake than normative appeals to professional ethics alone.