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Abstract Radiotherapy and targeted therapy are essential treatments for patients with brain metastases from human epidermal growth factor receptor 2 (HER2)-positive breast cancer. However, the combination of radiotherapy and targeted therapy still needs to be investigated, and neurotoxicity induced by radiotherapy for brain metastases has also become an important issue of clinical concern. It remained unclear how to achieve the balance of efficacy and toxicity with the application of new radiotherapy techniques and new targeted therapy drugs. This article reviews the benefits and potential risk of combining radiotherapy and targeted therapy for HER2-positive breast cancer with brain metastases.

Kernel adaptive filters (KAFs) have sparked substantial attraction for online non-linear learning applications. It is noted that the effectiveness of KAFs is highly reliant on a rational learning criterion. Concerning this, the logarithmic hyperbolic cosine (lncosh) criterion with better robustness and convergence has drawn attention in recent studies. However, existing lncosh loss-based KAFs use the stochastic gradient descent (SGD) for optimization, which lack a trade-off between the convergence speed and accuracy. But recursion-based KAFs can provide more effective filtering performance. Therefore, a Nyström method-based robust sparse kernel recursive least lncosh loss algorithm is derived in this article. Experiments via measures and synthetic data against the non-Gaussian noise confirm the superiority with regard to the robustness, accuracy performance, and computational cost.

Abstract Phase‐change random‐access memory (PCRAM) devices suffer from pronounced resistance drift originating from considerable structural relaxation of phase‐change materials (PCMs), which hinders current developments of high‐capacity memory and high‐parallelism computing that both need reliable multibit programming. This work realizes that compositional simplification and geometrical miniaturization of traditional GeSbTe‐like PCMs are feasible routes to suppress relaxation. While to date, the aging mechanisms of the simplest PCM, Sb, at nanoscale, have not yet been unveiled. Here, this work demonstrates that in an optimal thickness of only 4 nm, the thin Sb film can enable a precise multilevel programming with ultralow resistance drift coefficients, in a regime of ≈10−4–10−3. This advancement is mainly owed to the slightly changed Peierls distortion in Sb and the less‐distorted octahedral‐like atomic configurations across the Sb/SiO2 interfaces. This work highlights a new indispensable approach, interfacial regulation of nanoscale PCMs, for pursuing ultimately reliable resistance control in aggressively‐miniaturized PCRAM devices, to boost the storage and computing efficiencies substantially.

Objective： A tomato weight detection method based on image processing was established to realize non-contact tomato weight detection. Methods： The binary image of tomato was obtained through image processing. The geometric features of tomato were extracted by pixel statistics and minimum circumscribed rectangle method, and correlation analysis was made between the characteristics and the real value of tomato weight, then the regression model of tomato weight detection with geometric features as parameters was established. Results： Compared with the real size of tomato, the measurement error of transverse and longitudinal diameter of Tomato by minimum external rectangle method was less than 3%. In addition to fruit shape index, other geometric characteristics were linearly correlated with tomato fruit weight, and the correlation between positive characteristics and fruit weight was more significant. Three types of 20 models were established for prediction and evaluation. The multiple regression model with the parameters of tomato front projection area and perimeter, projection area of a side image and tomato transverse diameter had the highest accuracy, the regression coefficient was 0.962, the average relative error of detection value was 0.673%, and the average absolute error was 1.425 g. Conclusion： The model is suitable for the weight detection of tomatoes and other fruits or articles with similar axisymmetric shape characteristics.

The rapid development of artificial intelligence (AI) has brought new opportunities for cancer prevention and control. This review give a brief overview of the origin and basic elements of AI. Then it comprehensively carded the application of AI systems in the field of cancer, reviewed the important research progress of AI in several major types of cancer around image-based cancer screening and diagnosis. Finally, this review summarized the challenges in algorithm, implementation and ethics and future development as well as more ideas for the application of AI technology in the oncological research.

Developing highly efficient electrocatalysts for the CO2 reduction reaction (CO2RR) has attracted increasing interest in the past decade. Herein, we report on the design and synthesis of Fe porphyrin 1 with an appended N,N-di(2-picolyl)ethylenediamine (DPEN) unit that boosts electrocatalytic activity for CO2-to-CO conversion in acetonitrile with water as the proton source. By mimicking carbon monoxide dehydrogenase (CODH), 1 has poly-pyridine/amine units located at the active site to form hydrogen-bonded water-containing networks that enable fast proton transfer. The protonated and positively charged DPEN unit can also stabilize CO2 reduction intermediates through electrostatic and hydrogen-bonding interactions. These factors make 1 a highly active electrocatalyst for the CO2RR by achieving a TOFmax of 5.0 ​× ​104 ​s−1 with water providing the protons. These critical roles of the DPEN unit in the CO2RR are further supported by theoretical studies. This work is significant to highlight the benefits of using molecular catalysts to elucidate structural effects.

Abstract Background Understanding resident physicians’ perceptions of competency-based medical education(CBME) may help improve approaches for implementing such education in standardized resident training (SRT). We conducted surveys of residents in China to identify their perceptions of CBME and determine the degree to which such education impacts their career plans. Methods Questionnaire contained a total of 24 questions, which were answered using multiple choice or yes/no, was distributed to residents who were undergoing SRT, regardless of specialty, at 7 accredited training bases located across six provinces of China. The survey aimed to investigate residents’ reasons for participating in SRT, perceptions of CBME, interest in receiving CBME-associated courses, and attitudes towards CBME. Results Overall, 441 residents completed the questionnaire.17.7% (78/441) responded “no clear objective” before the participated in SRT. Only 3.9% (17/441) fully understood the objectives, training contents, and assessment system of the current “competency-based” standardized training program for residents in China. Residents ranked clinical skills and patient care, interpersonal communication, and professionalism, as the three most important competencies. Most were interested in the CBME residency programs. 90.7% felt that implementing CBME could help them clarify their professional direction and improve their career planning. Conclusion Residents had positive perceptions of the incorporation of CBME into SRT. Administrators, educational leaders, and clinical faculty should seek to further publicize and increase the popularity of CBME.