software testing

IMPACT OF PROXIMAL RELATIONSHIPS ON DRUG USE: A STUDY IN THERAPEUTIC COMMUNITIES

Drug use is an ancient practice, but its associated disorders represent a contemporary public health challenge. This study investigates the impact of proximal processes in childhood/adolescence and adulthood on substance use, focusing on the role of Therapeutic Communities (TCs). Using a qualitative methodology, 19 residents of TCs in the state of Rio de Janeiro were interviewed. Instruments included a screening test (ASSIST), a sociodemographic inventory, and semi-structured interviews. Content analysis of the interviews was supported by the Requalify.ai software, which proved to be an efficient tool for categorizing and visualizing qualitative data. Results indicate that factors such as dysfunctional family environments, violence, and early onset of consumption, often mediated by peer influence, are determining risk factors. On the other hand, peer social support within TCs emerges as a crucial protective factor, associated with positive changes reported by participants. The sample revealed an overrepresentation of Black and Brown individuals, highlighting the racial dimension in the history of drug use in Brazil. The study concludes that proximal relationships are decisive in both the etiology and recovery of substance use disorders, and that TCs, although controversial, can offer a supportive environment that favors change, especially through peer support and cohabitation.

Designing of a Currency Counting System with Integrated Counterfeit Currency Detection

The findings demonstrate that a software-based prototype integrating machine learning with image analysis can effectively simulate the core functions of a physical counterfeit-detecting banknote counter.

A framework for identifying turbulence periods with the relative financial Reynolds number: case study on six construction projects

This study proposes a framework for identifying financial turbulence in construction project cash flows using the Relative Financial Reynolds Number (Re(t)). Inspired by fluid mechanics, the indicator captures transitions between stable, high-risk, and turbulent financial regimes and provides an early-warning mechanism for identifying liquidity stress in construction projects. Daily cash flow data from six residential construction projects in Izmir, Türkiye, were analyzed. The Relative Financial Reynolds Number was calculated as the ratio between cumulative cash flow and its daily rate of change, following an analogy derived from Bernoulli-type financial flow models. Financial regimes were classified using statistical boundaries based on the mean and standard deviation of Re(t). The empirical performance of the indicator was evaluated through ROC analysis, lead-time analysis, and Monte Carlo simulation. The results show that Re(t) captures financial turbulence periods more sensitively than conventional S-curves. ROC analysis yielded AUC values between 0.49 and 0.78 across projects, with a pooled AUC of 0.64, indicating moderate classification capability. Lead-time analysis suggests that turbulence signals appear approximately 2–3 weeks before liquidity stress events on average. Monte Carlo simulations further indicate a 60-day stress probability ranging between 0.75 and 0.90 across projects. The empirical analysis is limited to six projects within a single national context. Future research should test the model across different countries and project types and explore additional statistical validation techniques to strengthen the theoretical foundations of the approach. The six-project analysis demonstrates that Re(t), compared to conventional S-curves, more distinctly differentiates stable periods, risk clusters, and extreme turbulence regimes. It provided early indications of the impact of macroeconomic shocks (interest rate hikes, currency crises, political transitions) on project financing, while also capturing legal, parcel-based, and site-specific disruptions directly in the time series. As such, Re(t) functions as an effective early-warning mechanism for project managers, offering insights that cumulative S-curves alone cannot provide. These results strongly support the study’s main hypothesis that Re(t) serves as a more sensitive and responsive indicator of financial risks in construction projects. The primary contribution is the demonstration of the applicability of Re(t), derived from a hydraulic analogy, to project finance. This approach enables project managers to monitor not only cumulative progress but also daily volatilities and critical boundary exceedances. Thus, Re(t) can serve as a signal detection mechanism contributing to risk management.Secondly, project managers should integrate Re(t) into daily or weekly reporting to detect risks more quickly. Re(t) boundary exceedances should be carefully monitored, especially during interest rate shocks, currency crises, and liquidity shortages. Integration of the Re(t) algorithm into project finance software could facilitate practical applications. The study introduces an interdisciplinary analytical framework that connects fluid mechanics and construction finance. By conceptualizing cash flow dynamics through the Relative Financial Reynolds Number, the proposed method provides a practical early warning tool for monitoring financial turbulence in construction projects.

Predicting patient satisfaction with post-small incision lenticule extraction surgery using open-source machine learning software.

A cross-sectional latent class analysis of depressive and anxiety symptoms in people aged 65 and older: Identifying subgroups and related factors.

Key factors contribute to differences in depression and anxiety symptoms among older adults: gender, body mass index, ethnicity, occupation before retirement, marital status, physical disability status, independence in activities of daily living, number of chronic diseases, smoking and drinking habits, dietary habits, recreational activities, physical activity, and sleep quality.

An in silico framework for dissecting the mechanistic origins of in vivo recorded neuronal activity.

Making ISF available as a standalone online resource, it is believed it will facilitate the generation, simulation and analysis of models that reveal mechanistic origins of in vivo recorded activity beyond the barrel cortex for which it was originally designed.

Evaluating the relationship between C-peptide levels and insulin resistance in patients with and without diabetic complications.

C-peptide can be used as an appropriate index for identifying IR in T2DM patients with complications and illustrated the clinical utility of C-peptide in microvascular complications such as diabetic nephropathy and diabetic retinopathy.

Evaluation of Alysis-001 cuffless blood pressure estimation algorithm against the European Society of Hypertension awake/asleep test criteria in hypertensive patients.

This represents the first evaluation of a Device Type 3 cuffless blood pressure algorithm (automated, wearable, demographic-calibrated, not at heart level) meeting ESH awake/asleep test criteria, suggesting Alysis-001's potential as a clinically viable alternative for ambulatory blood pressure monitoring in hypertensive patients.

Factors Associated with Prescription-to-Vaccination Conversion and Timeliness: A Real-World Analysis

Manual prescriptions and vaccination clinics were associated with higher vaccine prescription conversion, with particularly pronounced effects on non-NIP vaccines.

Micro‐Parameter Sensitivity Analysis and Validation of the Mechanical Behaviour of Soft–Hard Composite Rock Based on 2D‐DEM

Calibration of microparameters in numerical simulations is a critical factor affecting model accuracy. To determine the relationship between macro‐ and microparameters in composite rock masses and the influence of soft rock layer proportions on mechanical properties, this study employed PFC2D software to construct numerical models of composite rock masses with varying soft‐to‐hard layer thickness ratios. A systematic analysis was conducted to investigate the influence of microparameters on macro‐mechanical properties. For composite rock bodies with varying soft rock layer thicknesses, as the soft rock proportion increases, the failure mode gradually shifts from shear failure dominated by hard rock to foliated failure dominated by soft rock. Cracks propagate along bedding planes and are constrained by hard rock layers. When the soft rock layer thickness increases from 10% to 90%, the total number of cracks increases by approximately twofold, while the proportion of shear cracks decreases from 75% to 40%. The crack counting rate exhibits exponential growth with stress and synchronizes with stress amplitude, peaking at 180–200 times/s − 1 . Laboratory test results align with numerical simulations, demonstrating that the PFC model accurately predicts composite rock mass strength (error ≤3.7%) and elastic modulus (error ≤4.6%). This study provides theoretical support for correlating macro‐ and micro‐mechanical properties in composite rock masses of varying hardness, offering significant reference value for stability assessment and reinforcement design in underground engineering.

Fully automated analysis of cardiotoxicity surveillance echocardiograms: A direct test-retest precision comparison with experts

In cancer patients at risk of cardiotoxicity, the precision of 2D echocardiographic AI analysis exceeds that of experts, matching that of 3D LVEF assessment.

ASSESSMENT OF INCOME DIVERSIFICATION LEVELS AMONG SMALL-SCALE FARMERS IN YOBE STATE

This study aims to assess the level of income diversification among Yobe State small-scale farmers. Primary data was collected through a face-to-face survey-based approach through a multistage sampling technique, where 384 small-scale farmers were interviewed. The data were analyzed using statistical package for social science software (SPSS) version 26 for the descriptive analysis of the frequency distribution table, regression analysis and the Simpson Index of Diversification (SID) to test the study's aims and objectives. The results revealed that the respondents engaged in both On-farm and Non-farm livelihood diversification strategies. The overall SID of Non-farm diversification indicated that the respondents had a medium diversification index of 0.55, this primarily driven by participation in wage employment outside agriculture and self-employment. The on-farm diversification index was 0.30, indicating lower diversification than the Non-farm. This lower index is determined mainly by both food crops and cash crops. The study further revealed that small-scale farmers income diversification is influenced by the predictor factors of the farming operation system, average annual income in naira, age, farmland ownership, marital status, farm size, educational level, household size, and farming experience. The study concluded that the lower diversification index of On-farm could be due to the unpredictable risks associated with farming, making it less viable and turning farmers to off-farm activities as a means of coping strategies. And the Non-farm has a medium diversification index. This shows how important Non-farm is in stabilizing small-scale farmers' income and livelihood and signifies the potential risk facing the agricultural productivity in the study area.