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Perceptions of Chinese higher-vocational nursing program directors on digital transformation: A qualitative study
Background Currently, most research on digital transformation in higher vocational education conducts macro-level analyses, and few comprehensive studies specifically address higher vocational nursing education. Moreover, research is notably lacking on the perceptions of Chinese higher vocational nursing program directors, and the prevalent utilization of digital tools within this field remains underexplored. Objective To understand the perceptions and experiences of higher vocational nursing program directors regarding the use of digital transformation tools in nursing education. Methods This qualitative study employed semistructured interviews conducted with 14 program directors from higher vocational nursing programs. The interview data were transcribed, and Colaizzi’s seven-step method was used for a subject analysis. Results The study employed Colaizzi’s seven-step framework for inductive thematic analysis, with coding conducted collaboratively until data saturation was achieved. Analysis revealed four principal themes: (1) Recognition of digital education by program directors, where enthusiasm for enhanced engagement and transcended geographical barriers coexisted with unspoken doubts about resource quality and the authenticity of student participation; (2) Perceived status and impact of digital infrastructure, characterized by significant hardware investments yet inconsistent resource quality and utilization—revealing a fundamental gap between technological abundance and meaningful pedagogical integration; (3) Systemic Tensions and Barriers, exposing profound contradictions between policy aspirations and classroom realities, generational divides in educational philosophies among teachers, and persistent disconnects between technology’s promise and its operational friction, all of which contributed to increased workloads and a pervasive sense of professional role dissonance; (4) Strategic Approaches to Digital Transformation, centered on increasing investment, fostering educator development, promoting resource sharing, and strengthening industry-education integration. Conclusion Higher vocational nursing program directors recognize the value of digital education, yet its adoption is constrained by challenges in platform usability and a lack of supportive institutional incentives. Effective transformation requires systemic strategies that enhance the digital ecosystem's ease of use, align professional rewards with innovation, and promote cross-sector collaboration to develop pedagogically sound resources.
When collaboration fails: persuasion driven adversarial influence in multi agent large language model debate
Correction to “Dimensionality Reduction of Formamidinium-Rich Lead Iodide Perovskite-Derived Structures”
Programming Mat-Poka-yoke system control effect of unsteady convection-diffusion behavior for plastic manufacturing mathematically
The blowing and drying stages in the plastic manufacturing process generate many defects due to a lack of accuracy in estimating thermal convection and its diffusion control. Therefore, dual digital poka-yoke simulator phases have been built to describe the unsteady state of convection-diffusion mathematically (i.e., parabolic behavior), and converted to ordinary type using a discrete singular convolution transformer. The numerical solution improves the mechanism of JRNS (Jidoka recruit’s network system) to be easily programmed to be highly controlled. The mathematical poka-yoke simulator formulation relies on Runge-Kutta 4 th order and five-stage fourth-order robust stability protective Runge-Kutta (SSP-RK54) schemes as discussed in 1 st phase and called Mat-Poka-Yoke system (Mat-PYS) alternating between three stages. The accuracy of the Mat-PYS has been tested via measuring the rate of convergence, the absolute error, the L2 error, and the L∞ error, with errors up to 1 × 1 0 − 5 . The obtained outcomes are described both in tabular and graphical form, which almost includes the validity of these mechanisms to hold on to the precision, efficiency, simplicity, and applicability for solving convection-diffusion equations. The applicability emphasized via parametric analysis to debate the effect of convective velocities, diffusion coefficients, and time at different locations on results to resist the defect causes generation as demonstrated in 2 nd phase. The OEE for plastic injection machine process has been improved from 76.6% to 88.9% when controlled by proposed mechanism, and products quality improved to 5.2 sigma level.
First Zagreb energy of self-looped graphs: predictive insights into kidney infection drugs and theoretical bounds
Abstract Graphs containing self-loops provide a versatile framework for modeling heteroatomic molecules, with each self-loop representing a hetero-atom. In this study, we investigate the predictive capability of the first Zagreb energy in relation to the physicochemical properties of kidney infection drugs, using their corresponding molecular graphs with self-loops. The analysis using linear, quadratic, cubic, and logarithmic regression models reveals a strong correlation between the first Zagreb energy and key physicochemical properties such as polarizability, molar refractivity, and molar volume. Statistical metrics such as standard error (SE), F-test value, standard error of fit (SF), and root mean squared error (RMSE) validate the stability and reliability of the proposed models. Furthermore, we compute the first Zagreb energy of the complete graph $$(K_{n})_{_S}$$ , as well as the complete bipartite graph $$(K_{m,n})_{_S}$$ , with partite sets $$M=S$$ , and N . In addition, we derive both lower and upper bounds for the first Zagreb energy of graphs with self-loops.
Correction to “Hierarchical Tuning of the Performance of Electrochemical Carbon Dioxide Reduction Using Conductive Two-Dimensional Metallophthalocyanine Based Metal–Organic Frameworks”
Text encryption through bio-inspired DNA and RNA sequencing
Cryptography is the technology of protecting information and communication by means of encoding the sending information. Existing methods often operate within predetermined mathematical structures which can be subject to pattern recognition and which are lack biological randomness. To address these challenges, this paper introduced a new bio-inspired cryptography approach to protect text messages using the coding mechanisms of DNA and RNA materials. The encryption system consists of six steps: encoding the plaintext message into DNA sequences, transcribing DNA into RNA, applying the complementary base pairing, scrambling RNA segments, optional reverse transcription, and encoding the resulting DNA-RNA characters into ciphertext. Randomization is used in the encoding of DNA and in the scrambling of RNA to make each encryption instance different from the other. This method was tested with varying sizes of messages, and it has proved very efficient in terms of time between encryption and decryption. This approach has created new opportunities for the creation of new classes of secure cryptographic systems bio-inspired to get modern methods of digital communication.
Identifying symptom communities and core symptoms in the anxiety-depression network among computer science students
Abstract Although the mental health of college students has become a focus in the health field and society, there is still little discussion about the mental health of students in computer science and related majors. This study was guided by the network theory of mental disorders, presents a symptom network analysis of anxiety and depression among computer science students. A total of 3934 computer science students were included in this study. The seven-item Generalized Anxiety Disorder Scale (GAD-7) and the nine-item Patient Health Questionnaire (PHQ-9) were used to measure anxiety and depression symptoms. The connection between Nervousness and Uncontrollable worry is the strongest edge in the network. We identified the three core symptoms with the highest node strength were concentration, fatigue and psychomotor problems. The three bridge symptoms with the highest bridge strength were irritability, feeling afraid and psychomotor problems. Four well-characterized symptom communities were identified through the SpinGlass algorithm, including the core anxiety symptom community, the anxiety somatization manifestation symptom community, the core depressive symptom community, and the depressive physiological manifestation symptom community. The network performed well in both stability and accuracy tests. These findings are important for future interventions and improving the role of mental health issues for students with diverse majors and stressors.
Investigating the Intrinsic Activity, Nature, and Deactivation Pathway of a Carbon-Nanotube-Confined Molecular Co Catalyst for CO <sub>2</sub> Reduction
Nationwide monthly burned area monitoring in Indonesia using Sentinel-2
Wildfires pose a major challenge for many nations. Rapid mapping of their extent is key to evaluating their impacts. We present the first operational monthly burned-area processing chain for Indonesia, based on largely automated processing of Sentinel-2 imagery in Google Earth Engine. Our approach uses a Random Forest applied to Sentinel-2 imagery and integrates FIRMS fire hotspots to reduce false positives. The resulting 20-m monthly burned-area maps cover the entire country. From January 2019 to December 2024, fires burned a cumulative 5.62 million hectares (Mha), including 2.92 Mha that burned once and 1.12 Mha that burned multiple times. This represents a total burned extent of 4.04 Mha. Compared to the MCD64A1 product, our dataset detects more burns with higher spatial detail and accuracy. In total, 122,164 hectares of primary humid forest burned, representing 2.2% of the burned area. In 2019 and 2023, fire activity accelerated around July and peaked in September–October, coinciding with Oceanic Niño Index (ONI) values ≥ +0.5 °C and Indian Ocean Dipole (IOD) values ≥ +1.5°C. In contrast, neutral or negative phases from 2020 to 2022 corresponded with minimal burning. The year 2024 recorded intermediate fire activity without strong climatic anomalies. These findings confirm that climatic anomalies are associated with fire activity in Indonesia, reaffirming the importance of ONI and IOD for early warning. Our results suggest that prevention efforts are limiting forest fires, as burns in 2019 and 2023 remained lower than during earlier events. Monthly burn-scar updates are available on Nusantara Atlas ( www.nusantara-atlas.org ), an open-access platform for monitoring deforestation in Southeast Asia.