Enhancing and Improving Resident Doctor Handover Practices at Black Country NHS Foundation Trust by Farzana Rahman, Aradhana Gupta, Oluwakemi Olaoye, Nargis Uddin Amir, Pallavi Chandra

“…Poor communication during shift transitions is a major contributor to medical errors and adverse events. …”
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Reinforcement-Learning-Based Trajectory Design and Phase-Shift Control in UAV-Mounted-RIS Communications by Tianjiao Sun, Sixing Yin, Li Deng, F. Richard Yu

“…However, the online interaction between the agent and environment may lead to instability during the training and the assumption of (first-order) Markovian state transition could be impractical in real-world problems. …”
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Data efficient prediction of excited-state properties using quantum neural networks by Manuel Hagelueken, Marco F Huber, Marco Roth

“…For these molecules, we predict the excited state transition energies and transition dipole moments. We show that, in many cases, the procedure is able to outperform various classical models (support vector machines, Gaussian processes, and NNs) that rely solely on classical features, by up to two orders of magnitude in the test mean squared error.…”
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Phase Diagram of Extensive-Rank Symmetric Matrix Denoising beyond Rotational Invariance by Jean Barbier, Francesco Camilli, Justin Ko, Koki Okajima

“…We also argue that it is only beyond the transition that factorization, i.e., estimating X itself, becomes possible up to irresolvable ambiguities. …”
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Nickase fidelity drives EvolvR-mediated diversification in mammalian cells by Juan E. Hurtado, Adam J. Schieferecke, Shakked O. Halperin, John Guan, Dylan Aidlen, David V. Schaffer, John E. Dueber

“…Here, we engineer CRISPR-guided error-prone DNA polymerases (EvolvR) to diversify all four nucleotides within genomic loci in mammalian cells. …”
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Die makromolekulare Charakterisierung der Gelatine by I. Tomka

“…Beginning with the dilute gelatin solution at a temperature above the helix-coil transition it is shown that the molecular mass distribution could be evaluated by the combined application of preparative gel chromatography and acrylamide gel electrophoresis. …”
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Multivariate temperature-series analysis of stress-induced ferroelectricity in SrTiO3: a machine learning approach with K-shape clustering and hierarchical Bayesian estimation by Hirotaka Manaka, Kensei Toyoda, Yoko Miura

“…In addition, to obtain the structural and ferroelectric phase transition temperatures, [Formula: see text] and [Formula: see text], hierarchical Bayesian temperature-series estimation was performed at each pixel (as a lower level) constrained over the entire cluster (as a higher level) considering the measurement error. …”
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Harnessing laboratory data for poliovirus eradication: contributions of the Africa regional polio laboratory data management team, 2022 – 2024 by Brook Tesfaye, Reggis Katsande, Doungmo Wakem Yannick Arthur, Julius E Chia, Chefor Ymele Demeveng Derrick, Ikeonu Obianuju Caroline, Kabore Sakma, Mahmud Zubairu, Busisiwe Ngobe, Abdulahi Walla Hamisu, Ticha Johnson Muluh, Kebba Touray, Modjirom Ndoutabe, Jamal A Ahmed, Anfumbom Kfutwah

“…Efforts to transition to the Web-based Information for Action (WebIFA) system and capacity building through training workshops have further strengthened data management and surveillance capabilities across the region. …”
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Research on Model Reconstruction Methods for Partial Point Cloud Information Loss by Zhengping CHANG, Guoshuai YUAN, Jiuhua LI, Yang ZHAO, Zhongqi WANG

“…In contrast, the model reconstructed using the proposed method exhibited a smooth transition area, ensuring surface continuity. The deviation cloud map comparing the theoretical model with the complete point cloud indicated a maximum deviation of 0.802 mm, representing the largest error in 3D-printed part manufacturing in the middle of the outer cylinder. …”
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Causes of the Outer Spiral Rainbands in Typhoon Yagi （ 2018） in Shandong Province of China by Chunyan SHENG, Sudan FAN, Qiaona QU, Shijun LIU, Wengang ZHU

“…On August 14， 2018， Typhoon Yagi （2018） moved northward and impacted Shandong Province of China， resulting in widespread rainstorm and heavy rainstorm.The total rainfall caused by the typhoon in Shandong presents a round-shaped distribution.Specifically， on August 14， an outer spiral rainband appeared on the typhoon periphery in southeastern Shandong， bringing short-term heavy rainfall and local heavy rainstorms.Due to the relatively small scale of this rainband， both numerical forecasting models and forecasters face challenges in predicting its rainfall accurately.To study the mechanisms of the outer spiral rainbands of Typhoon Yagi， the characteristics and causes of the spiral rainbands are investigated in this study by using radar data and the observations from ground-based stations， radiosonde stations and aircraft.Numerical experiments are also conducted based on the Advanced Research WRF （Weather Research and Forecasting） model and its Hybrid-3DVAR （three-dimensional variational） data assimilation system.The model adopts 12 km and 4 km one-way nested grids， with 44 vertical layers.The initial ensemble perturbation fields are generated by using a stochastic perturbation method， and the Ensemble Transform Kalman Filter （ETKF） method is used for the bias correction of ensemble forecast， providing flow dependent background errors for the Hybrid-3DVAR assimilation module.Comparative experiments with and without the Aircraft Meteorological Data Relay （AMDAR） data assimilation are conducted by adopting 100% flow-dependent error covariance and by using a 45-minute assimilation time window.The results indicate that the outer spiral rainbands are formed by the merging and development of several linear mesoscale convective systems （MCSs）.The outer spiral rainbands exhibit distinct characteristics of the linear MCSs with leading stratiform precipitation， i.e.， the linear MCSs consist of several convective cells with back-building convection.There are several stronger linear MCSs merging laterally into other linear MCSs.Broad stratiform echoes appear in the front （eastern part） of the linear MCS in its maturity stage， and the convection develops up to 10 km or more.There is a weak-echo transition zone between the strong convective line and the sub-strong stratiform echo region.Short-term heavy rainfall occurs along the linear MCS at the maturity stage.The water vapor of heavy rainfall mainly comes from the near-surface layer （below 850 hPa） around the typhoon， and the water vapor flux convergence is mainly concentrated near the wind field convergence line.Before convection initiation， the middle and lower levels over Shandong are thermally unstable with high temperature and high humidity， and the wind rotates clockwise with height， which favor the development of convective systems.As the typhoon slowly moves northward， downward intrusion of cold air appears at 500 hPa.Below 900 hPa， on the southeast of the typhoon over central Shandong there are local convergence between southwesterly wind and southerly wind， and between southerly wind and southeasterly wind.The convergence-induced dynamic uplift triggers the release of unstable energy， stimulating several local linear MCSs.The MCSs develop northward along the steering flow.The linear MCSs merge and strengthen for several times， and finally the elongated spiral rainbands occur.During the convection lifetime， the updrafts are noticeably stronger than the downdrafts.At the mature stage of the convective systems， dry and cold downdrafts appear in the lower levels in the front of the MCS.Convective systems at the heights above 600 hPa move rapidly eastward with the upper-air steering flow， leading to the gradual weakening and dissipation of the linear MCS.Assimilation of AMDAR can improve the typhoon track and wind field forecasts of the WRF model， as well as the dynamical triggering mechanism of convective systems.Thus， the occurrence of spiral rainbands in the typhoon periphery could be accurately forecasted.Furthermore， central Shandong is a mountainous region， so how does the topography influence the triggering and developing of convective systems？ …”
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Optical Analysis of Dry Reforming of Methane in Microwave-Induced Plasma at Atmospheric Pressure by Xiuqiang Zhang, Nobusuke Kobayashi, Yoshinori Itaya

“…The most prominent peak corresponded to the energy excitation of Ar (II) ions at 388.03 nm, and the atomic transition process was 3s23p4(3P)4d4D1/2 → 3s23p4(3P)4p4D°1/2. …”
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Engineering qubit dynamics in open systems with photonic synthetic lattices by Francesco Di Colandrea, Tareq Jaouni, John Grace, Dilip Paneru, Mirko Arienzo, Alessio D'Errico, Ebrahim Karimi

“…We experimentally validate this method by simulating common noise processes, such as phase errors and depolarization. Besides providing a practical solution for quantum state purification, this work demonstrates a versatile approach for the simulation of open qubit dynamics, with potential implications for quantum error correction and environment-induced quantum phase transitions.…”
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A Conceptual Framework for User Trust in AI Biosensors: Integrating Cognition, Context, and Contrast by Andrew Prahl

“…We then derive practical implications such as enhancing interpretability, tailoring data presentations to task demonstrability, and implementing transitional introduction phases. The framework offers researchers, engineers, and clinicians a structured conceptual framework for designing and implementing the next generation of AI biosensors.…”
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Assessing the impact of sampling bias on node centralities in synthetic and biological networks by Ali Salehzadeh-Yazdi, Marc-Thorsten Hütt

“…We simulate six types of biased down-sampling, transitioning networks from dense to sparse states, using the initial network as the ‘ground truth.’ …”
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UWB and GNSS Sensor Fusion Using ML-Based Positioning Uncertainty Estimation by Mihkel Tommingas, Taavi Laadung, Sander Varbla, Ivo Muursepp, Muhammad Mahtab Alam

“…The results show that the ML-based approach can improve seamless transition between indoor and outdoor areas with almost no sensor dropouts with a mean positioning error of 0.16 m and a maximum error of approximately 0.5 m.…”
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Noise resilience in adaptive and symmetric monitored quantum circuits by Moein N. Ivaki, Teemu Ojanen, Ali G. Moghaddam

“…These systems exhibit entanglement and purification phase transitions, along with various symmetry-enforced and ordered non-equilibrium phases. …”
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Sunrise in the Desert: Leveraging Big Data Analytics for Predictive Solar Energy Production in Saudi Arabia by Da'ad Albahdal, Maha Almousa, Wijdan Aljebreen, Aeshah A. Almutairi

“…This research addresses the critical need for accurate solar energy forecasting in Saudi Arabia’s renewable energy transition. Leveraging the comprehensive Solar Resource Monitoring Stations dataset (2017–2021) from King Abdullah City for Atomic and Renewable Energy, this study presents the first extensive analysis of solar stations across Saudi Arabia with a systematic classification of solar stations into five distinct geographical groups, accounting for regional climate variations and solar radiation patterns. …”
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Key Perception Technologies for Intelligent Docking in Autonomous Modular Buses by Ye Xiao, Yuxuan Zheng, Xin Liu, Yifen Ye

“…Autonomous modular buses (AMBs) constitute a novel form of public transportation, enabling real-time adjustments of module configurations and facilitating passenger exchanges in transit. This approach resolves unpleasant transfer experiences and offers a potential solution to traffic congestion. …”
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Health State Prediction of Lithium-Ion Battery Based on Improved Sparrow Search Algorithm and Support Vector Regression by Deyang Yin, Xiao Zhu, Wanjie Zhang, Jianfeng Zheng

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Stator grounding fault severity characterization and novel inverse-time protection method for large generators by Yikai Wang, Jie Ou, Jian Qiao, Zengping Wang, Xianggen Yin, Chunguang Ren

“…Thus, the generator’s safety under high transition resistance grounding fault conditions can be guaranteed.…”
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