November 5 · Article · Healthcare · Public Health, Environmental and Occupational Health
Background/Objectives: Evidence-based clinical guidelines and standardized nursing documentation are essential for healthcare quality and safety, yet evidence on their use by nurses in Kazakhstan is limited. This study assessed the reported use of clinical guidelines and nursing documentation checklists. Methods: A cross-sectional online survey with convenience sampling was conducted from December 2021 to February 2022; 2263 practicing nurses were analyzed. “Use” meant self-reported use in routine practice. Proportions with 95% confidence intervals were calculated for the whole sample. Results: Reported use varied across clinical areas. Pressure ulcer guidelines were used most often (39.0%; 95% CI 37.0–41.0), followed by patient- and family-centered care (37.1%), fall prevention (34.3%), and anti-smoking interventions (31.3%). Among documentation checklists, reported use was highest for allergic reaction care (40.3%) and preventing injuries and falls (34.5%) and below 15% for care after a tracheostomy, duodenal probing, and gastric tube insertion in neonates and premature infants, which apply only to specific patient groups. Conclusions: In this convenience sample, reported use of guidelines and checklists was low to moderate and uneven. The findings are not national implementation rates. The study design does not allow the causes of this variability to be identified; the role of education, organizational support, and electronic documentation should be examined in future research.
BSBibinur SydykovaOpen access
November 11 · Article · Automation · Artificial Intelligence
Sulfur recovery units (SRUs) at oil refineries are complex, multi-parameter systems whose Cold Bed Absorption (CBA) reactors operate under incomplete and uncertain process information, which limits conventional control. This study develops an engineering neuro-fuzzy decision support system (DSS) for optimizing sulfur production at the Atyrau oil refinery (Kazakhstan) under uncertainty. The system integrates a mathematical description of the process, whose dynamic part is stated as a general formulation, an expert-derived fuzzy rule base, a first-order Sugeno neuro-fuzzy estimator of sulfur yield and quality, and a multi-criteria fuzzy optimization block based on the Bellman–Zadeh approach, together with an explicit operator-facing decision algorithm and a software interface. The estimators were identified and validated on 200 operating log records of the unit. These records show that the effect of reactor temperature on the sulfur quality index reverses sign with reactor pressure—the correlation is −0.57 below 0.79 kgf/cm2 and +0.75 above it—so that a model additive in the two variables cannot represent the relationship: linear regression on temperature and pressure attains a cross-validated R2 of only 0.06 for the quality index, whereas the neuro-fuzzy estimator attains 0.83 (RMSE 0.72 points, MAPE 0.74%). A regression with an explicit interaction term on the same inputs attains 0.79; in a paired comparison the neuro-fuzzy estimator had the lower error in every repetition, but the difference is not statistically significant (p = 0.07), and the estimator is retained for its rule-level interpretability and its integration with the decision block. For sulfur yield, where the relationship is close to linear once pressure and throughput are accounted for, the corresponding figures are 0.71 and 0.85 (RMSE 0.33 t/day, MAPE 1.35%). The same ordering is reproduced on an independent hold-out test set, under nested and cluster-blocked cross-validation and after removal of the records lying at the unit’s capacity and regulatory bounds, and the expert rule base was revised into an asymmetric form accordingly. A worked application of the optimization block to three operating situations, with the production plan, quality and capacity constraints enforced, raised the model-predicted degree of joint satisfaction of the yield, quality and energy criteria from 0.08–0.25 to 0.49–0.57; in one of the three, the recommended action is to reduce process severity and lower a reheat duty surrogate by about a third rather than to increase output. The resulting DSS, at present a standalone advisory software prototype, supports the operator in analyzing the current process state, evaluating alternative operating modes and forming recommendations, while the final decision remains with the operator.
BOBatyr OrazbayevOpen access
November 11 · Dataset · Figshare · Artificial Intelligence
This package accompanies the paper “Mystical-Aware but Not Always Accurate: Probing LLM Interpretation of Contested Images in Classical Uzbek Poetry (A Low-Resource Case Study)”. It contains a gold-set of 13 contested classical-Uzbek (Chagatai) poetic images, each with an example couplet from Alisher Navoi, a literal surface sense and an expert figurative/mystical reading drawn from published Uzbek commentary; the exact prompt and run settings used to probe DeepSeek (web interface, search and reasoning disabled, a fresh session per item, three runs); the raw model responses for all three runs; and the per-item verdicts behind the reported results (literal-collapse rate and error taxonomy). The couplets are public-domain classical poetry. See README.md for the file list and the scoring scheme.
GSGulnoza SalimovaOpen access
