GH4169 nickel-based superalloy exhibits excellent mechanical properties and has aroused wide interests in applications of aerospace engine components and transmission systems. Currently, Conventional grinding (CG)of GH4169 generates excessive heat, resulting in high grinding temperatures that can easily cause grinding burns. Ultrasonic vibration assisted grinding (UVAG)an advanced hybrid processing technology, enhances heat dissipation through the periodic variation in abrasive grain motion. It is considered an ideal method for reducing grinding temperature. However, the complex and intermittent contact between the UVAG workpiece and abrasive grains presents an essential challenge for accurate theoretical temperature prediction. To address this issue, the grinding temperature prediction model for UVAG was developed according to the Welch-Type (WT) heat source. On this basis, we performed grinding experiments for comparing temperature prediction accuracy of WT heat source with that of the conventional rectangular heat source model. According to our findings, WT heat source exhibits the maximum prediction error of 23.2
This article is devoted to the impact of the urbanized area of Naryn city on the water quality of the Naryn River. The studied river, which is 807 km long, serves as the main tributary of the Syr-Darya River and responds a key water artery of Central Asia. To assess the influence of anthropogenic activities, data on the chemical composition of surface water were collected from three monitoring stations over a five-year period (2019–2023). The results reveal significant variations in the concentration of cations, anions and heavy metals along the river’s course throw the city. The cation concentration indicates the predominant role of calcium ions (Ca2+), which is primarily due to their influx into aquatic systems as a result of the weathering of calcium-bearing rocks. Elevated concentrations of Ca2+ and Mg2+ observed at the second and third monitoring stations may indicate a potential influence of urban runoff and domestic wastewater on water quality. These finding highlight the need for improved wastewater management and сcontinuous water quality monitoring to preserve this critical freshwater resource. Furthermore, the study emphasizes the importance of implementing environmental protection measures to mitigate pollution risks and ensure sustainable water use in the region.
The study examines the relationship between the digital media environment, sociopolitical contexts, and information resilience in Muslim communities. The study is a systematic literature review and theoretical synthesis using comparative-historical, discursive, and systems approaches. The findings show that digitalization has transformed online space into a key sphere for religious practice and religious socialization, contributing to the emergence of “digital Islam.” Among young people, religious socialization and the choice of preachers increasingly occur online within “information cocoons.” In Central Asia, the influence of the internet and social networks has nearly equaled television: 56% of the population receive news from television and 50% from social networks, mainly via smartphones. Television remains dominant among people aged 55+, while younger audiences rely primarily on online sources. Young people, elderly people, and linguistic minorities are especially vulnerable to disinformation and manipulation and often become targets of Islamophobic and radical narratives. In Tatarstan, Islam is understood mainly as heritage or ethnic Islam, associated with Tatar identity and cultural heritage rather than strict ritual observance. States and organizations combine control measures with media-literacy programs, although excessive securitization can push users into closed online spaces and increase radicalization risks. The study concludes that digital technologies do not generate radicalism but accelerate its spread and transform its forms within the intersection of religion and security policy.
Purpose Small annual agricultural panels are vulnerable to validation leakage and silent performance loss when models are transferred to later years or unobserved regions. This study evaluates an auditable decision-support workflow that freezes model routing and review capacity before external testing. Methods Wheat yields for seven Kyrgyz oblasts (1991–2025) were combined with lagged temperature context. Development covered 1994–2014, calibration 2015–2018, and sealed evaluation 2019–2025 in five seen and two held-out oblasts. Persistence, three learned models, and calibration-frozen adaptive fallback routing (CAFR) were assessed using exact year-cluster inference, 21 spatial holdouts, interval stress tests, and enumeration of 7^7 equal-capacity review policies. Results Row-random validation understated future CAFR error by 30.2%. Across 49 predictions, random forest had the lowest pooled mean absolute error (3.43 centner ha − 1), followed by CAFR (3.54), ridge (3.56), and persistence (4.16). CAFR improved on persistence in four years, tied in three, and worsened in none; the one-sided exact p value was 0.0625. A nominal 90% frozen interval covered only 55.1% of external cases. Reviewing one highest-drift oblast per year examined 14.3% of cases and captured 33.0% of absolute error. Only 3 of 823,543 equal-capacity random policies matched or exceeded that capture (p = 3.64 × 10 − 6). Conclusion The contribution is a reproducible reliability audit and workload-control protocol, not evidence for autonomous yield forecasting. Exact small-sample inference, failure reporting, and bounded human review provide a defensible basis for sparse-data agricultural decision support.
Amid increasing climate instability and growing concerns over food security, the development of hydraulic infrastructure (HI) has become a key factor for the sustainable functioning of agriculture in the Talas region. This article presents a comprehensive analysis of the role of the existing irrigation system—including canals, pumping stations, and reservoirs—in ensuring water supply for more than 70
