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Developing Earth science data products that meet the needs of diverse users is a challenging task for both data producers and service providers, as user requirements can vary significantly and evolve over time. In this comment, we discuss several strategies to improve Earth science data products that everyone can use.

Objective To evaluate the application of micro-video combined questioning health education in the nursing of elderly patients with diabetes mellitus. Methods Totally 158 elderly patients with diabetes mellitus who admitted to the hospital during January and December 2023 were recruited using random number method, and were divided into control group (n=79) and observation group (n=79). The control group was given conventional oral health education, and the observation group was given micro-video combined with questioning health education. The health knowledge awareness, patients' treatment compliance, blood glucose level, and time required for health education were observed and compared between two groups. Results After the intervention, the health knowledge and treatment compliance of patients in the observation group were higher than that of the control group(P＜0. 01); The Fasting Plasma Glucose (FPG) and 2h Postprandial Glucose (PPG) levels were in the observaiaton group were lower than those of the control group(P＜0. 01). The time required for health education was significantly shorter than that of the control group(P＜0. 01). Conclusion Micro-video combined with questioning health education can effectively improve the diabetes knowledge awareness rate of patients, improve patients' treatment compliance, effectively control the blood sugar level, shorten the time required for health education, and improve the work efficiency of nurses, which is worthy of clinical promotion. (目的 探讨微视频联合提问式健康宣教在老年糖尿病患者护理中的应用效果。方法 选取医院2023年1月—12月收治的老年糖尿病患者158例, 采用随机数字法分为对照组(n=79)和观察组(n=79)。对照组给予常规口头式健康宣教, 观察组在对照组的基础上给予微视频联合提问式健康宣教。比较两组干预前后的健康知识知晓率、患者的治疗依从性、血糖水平和护士健康宣教所需时间。结果 干预后, 观察组患者的健康知识知晓率、治疗依从性均高于对照组, 空腹血糖水平、餐后两小时血糖水平均低于对照组, 护士健康宣教所需时间短于对照组, 差异有统计学意义(P＜0. 01)。结论 微视频联合提问式健康宣教用于老年糖尿病患者护理中, 能有效提高患者的糖尿病知识知晓率, 提高患者治疗依从性, 有效控制血糖水平, 同时也缩短了护士健康宣教所需时间, 提高了护士的工作效率, 值得临床推广。)

Super-gravity field was reported to strongly intensify the buoyancy-driven flow of liquid during solidification, affecting the solute convection and morphology of eutectic structure in binary alloys. In ternary eutectic alloys, certain two-phase regions with a coarse structure can usually be detected concurrently along with three-phase eutectics, leading to the formation of heterogeneous structure with limited ductility. Currently, Al–Ce–Ni ternary eutectic alloy was chosen as a modal system, which was reported for the first time to be solidified under super-gravity field with high volume fraction of three-phase eutectics. Meanwhile, the formation of ultrafine-fibrous interconnected Al11Ce3–Al3Ni eutectic clusters with more “chains” and higher spatial connectivity was detected mainly due to the relatively higher nucleation rate. The high volume fraction and refinement of interconnected Al11Ce3–Al3Ni eutectic clusters with excellent thermal stability could contribute to enhancement of ductility and tensile strength at elevated-temperature. Interestingly, the strength retention at 300 °C and 400 °C were able to reach up to ∼68.1 % and ∼33.2 %, respectively.

Under the background of economic and social transformation, it is of great significance to explore the interactive relationship between rural residential land structure and function and promote their adaptive development, which will reshape rural space and promote rural revitalization. On the basis of explaining the connotation of “interactive relationship between rural residential land structure and function”, this study analyzed the basic conditions and dynamic mechanism, process, and characteristics of the interaction between the two, constructed a theoretical framework, and explored the application directions of the theory. The study found that: (1) Interaction between rural residential land structure and function is a process of “factor-structure-function” adjustment caused by the internal and external environments of the rural residential land system, which is characterized by staged, self-adaptive and driven. (2) Affected by the rate of regional economic development, the transition degree of the economy, and the difference of social structures, the interactive relationship between rural residential land structure and function is not corresponding on the temporal and spatial scales, showing mismatch, competition, and synergy. (3) By carrying out rural space reconstruction, attaching importance to the projection of village function to material space, innovating mixed village planning, and improving relevant system support under the guidance of “function-led land use structure adjustment”, we can promote the coordinated adaptation of rural residential land structure and function.

C18H18N2O3S⋅C2HF3O2, monoclinic, P21 (no. 4), a = 6.0979(2) Å, b = 32.3052(9) Å, c = 11.0805(3) Å, β = 99.5620(10)°, V = 2152.46(11) Å3, Z = 4, Rgt(F) = 0.0570, wRref(F2) = 0.1470, T = 200(1) K.

Developing ultraflexible sensors using metal oxides is challenging due to the high-temperature annealing step in the fabrication process. Here, we demonstrate the ultraflexible relative humidity (RH) sensor on food plastic wrap by using 808 nm near-infrared (NIR) laser annealing for 1 min at a low temperature (26.2–40.8 °C). The wettability of plastic wraps coated with sol-gel solution is modulated to obtain uniform films. The surface morphology, local temperature, and electrical properties of the SnO2 resistor under NIR laser irradiation with a power of 16, 33, and 84 W/cm2 are investigated. The optimal device can detect wide-range RH from 15% to 70% with small incremental changes (0.1–2.2%). X-ray photoelectron spectroscopy reveals the relation between the surface binding condition and sensing response. Finally, the proposed sensor is attached onto the face mask to analyze the real-time human breath pattern in slow, normal, and fast modes, showing potential in wearable electronics or respiration monitoring. [ABSTRACT FROM AUTHOR]

In this study, taking the Jurassic Lianggaoshan Formation (J1l) tight sandstones in the eastern Sichuan Basin as an example, the types and well-logging responses of main sedimentological and diagenetic facies in the lacustrine delta-front are investigated based on summarizing the sedimentary characteristics and reservoir properties. Subsequently, further validation and application are conducted in the study area through machine learning. Research results show that the J1l lacustrine delta-front in the eastern Sichuan Basin mainly develops subaqueous distributary channels and mouth bar sand bodies, exhibiting typical densification reservoirs, with porosity and permeability distributed between 0.48% and 11.24% (av. 3.87%) and 0.0003–0.653 × 10−3 μm2 (av. 0.026 × 10−3 μm2), respectively. Strong compaction and strong cementation are the primary factors leading to densification, whereas chlorite coatings and weak dissolution play constructive roles in preserving some primary pores, creating a small amount of dissolution pores, and enhancing permeability. In terms of manifestation, the pore-throat content with a radius greater than 0.006 μm governs the reservoir quality. Furthermore, five types of diagenetic facies are identified in the J1l subaqueous distributary channels and mouth bars: strong compaction facies (Type I), strong cementation facies (Type II), chlorite-coating and intergranular pore facies (Type III), weak dissolution and intragranular pore facies (Type IV), and medium compaction and cementation facies (Type V). Overall, the thick and coarse-grained subaqueous distributary channels can be considered as the preferred exploration targets for tight oil and gas, with type III and type IV diagenetic facies being the most favorable reservoirs, characterized by well-logging responses of high AC and low GR, DEN, and RT. Based on the fine division of sedimentological and diagenetic facies, establishing well-logging interpretation models and then employing machine learning to achieve sweet spot reservoir prediction can provide valuable insights for tight oil and gas exploration in regions lacking core data.