Han Wang

This article proposes a real-time step-by-step method (SSM) based on an improved orthogonal basis function (IOBF) theory for 3D localization and magnetic moment (MM) estimation of multiple magnetic sources. SSM first determines targets’ X-coordinates by detecting peaks in rotationally invariant fusion energy, followed by a dual-fluxgate architecture to resolve Y- and Z-coordinates. After localization, MMs of all targets are jointly estimated via least-squares fitting. Unlike classical OBF methods, SSM eliminates reliance on the predefined CPA distance R₀ by accurately estimating it, suppresses error propagation, is immune to misalignment errors, and avoids inherent localization error. Compared with the state-of-the-art optimization method (OPM), SSM delivers superior accuracy and exceptional efficiency. Both simulation and field experiments consistently demonstrate that SSM achieves lower errors and over 20-fold faster execution than OPM. Performance in real-world high-noise environment further validates the accuracy and robustness of the proposed method. Rigorous mathematical derivations, implementation simplicity, and extremely fast execution highlight considerable potential of SSM for real-time remote sensing applications.

Purpose: This study compares the prevalence of occupational burnout, depression, and satisfaction with work-life integration (WLI) among U.S. residents and fellows (trainees) with that of U.S. physicians and the general U.S. workforce and examines the current point prevalence of burnout and satisfaction with WLI among trainees relative to 2012. Method: Between November 30, 2023, and January 2, 2024, U.S. trainees were surveyed using methods similar to a 2012 study. A sample of practicing U.S. physicians and a probability-based sample of the U.S. working population were surveyed at a similar timepoint. Burnout was assessed using the emotional exhaustion and depersonalization scales of the Maslach Burnout Inventory, depression using the Patient Reported Outcome Measurement Information System depression scale, and satisfaction with WLI with a previously used standardized item. Results: Surveys were completed by 3,486 of 58,127 trainees (6.0%). Nonresponder analysis suggested participants were representative of U.S. trainees with respect to burnout and depression. A higher proportion of trainees than practicing physicians had burnout symptoms (1,376 of 3,486 [50.0%] vs 3,023 of 7,643 [45.2%]; P < .001). In pooled analysis of trainees and similarly aged U.S. workers in other fields, adjusting for age, gender, and relationship status, trainees were at higher risk for burnout (odds ratio [OR], 1.51; 95% CI, 1.27-1.80) but lower risk for moderate or severe depression (OR, 0.80; 95% CI, 0.52-0.98). In pooled multivariable analysis of trainees from the 2012 and 2023 surveys, adjusting for year in training, relationship status, and specialty, trainees in 2023 had lower odds of burnout than those who responded in 2012 (OR, 0.71; 95% CI, 0.61-0.81). Conclusions: Burnout among U.S. trainees was lower in 2023 than 2012. Despite this improvement, trainees remain at higher risk for burnout than workers in other fields. Continued efforts are needed to optimize trainee education, preparedness for practice, and well-being.

Purpose: The Stanford Model of Occupational Well-Being (Stanford Model) hypothesizes that occupational well-being is driven by 3 reciprocally related domains: workplace efficiency, culture of wellness, and individual factors. The current analysis assesses the key elements of this model with cross-sectional empirical data. Method: In fall 2020 and spring 2022, well-being surveys were distributed to all Stanford School of Medicine clinical faculty working at 50% or more of full-time equivalent. A total of 1,909 clinical faculty were invited to complete the 2020 survey and 2,251 to complete the 2022 survey. The survey assessed burnout and professional fulfillment, along with 9 hypothesized determinants, as occupational well-being outcome indicators. Exploratory factor analysis was used to determine whether these determinants grouped well into the 3 domains described by the model. Domain scores were created based on factor analysis groupings of the scores for the determinants in each domain. Results: Of 1,909 clinical faculty invited to complete the 2020 survey, 1,479 (78%) participated. Of the 2,251 clinical faculty invited in 2022, 1,552 (69%) participated. The associations of the 3 domain scores with burnout and professional fulfillment were moderate for workplace efficiency ( r = 0.42–0.49; P < .001) and large for culture of wellness ( r = 0.51–0.63; P < .001) and individual factors ( r = 0.52–0.72; P < .001). Domain scores accounted for 45% and 50% of the variance in professional fulfillment and 56% and 58% of variance in burnout in 2020 and 2022 data, respectively. Conclusions: These results provide empirical evidence to support a widely adopted conceptual model of occupational well-being, including categorization of the hypothesized determinants of well-being into 3 domains, correlations among the domains, and association of the domain scores with burnout and professional fulfillment. Further research is needed to test causal relationships hypothesized by the model.

Efficient and accurate magnetic target localization methods have important value in navigation, archaeology and other fields. The current scalar positioning technology of magnetic target mainly adopts more than two scalar magnetometers to form a spatial gradient observation array. However, this method has some shortcomings, such as requiring multiple magnetometers, perpendicular gradient axes and appropriate baseline distance. Therefore, this letter proposes a method with a horizontal structured dual scalar magnetometers. Firstly, we construct a set of Anderson basis functions using the magnetic anomaly signals measured by two magnetometers respectively, and further solve them using an Improved Cuckoo Search (ICS) algorithm based on the idea of spiral update. Finally, the exact estimation of the target characteristic parameters is achieved by combining the spatial structure relationship of the two magnetometers. The proposed method greatly reduces the number of magnetometers required and does not need to consider the baseline distance and gradient axis non-vertical problems. Numerical simulation results show that the target depth is in the range of [10 m, 25 m], with a root mean square error (RMSE) of target position and magnetic moment below 0.4 m and 30 A·m ² , respectively. The results of field experimental data further demonstrate the effectiveness of the proposed method.

A high-resolution global magnetic gradient tensor (MGT) model is an essential tool for aided navigation. However, the high-order expansion using the traditional spherical harmonic (SH) method will lead to the non-convergence in calculating locations near the Earth’s polar regions, and poles are treated as singularities, making it challenging to meet navigation’s high-resolution requirements. This paper proposes a calculation method for the non-singular MGT model based on oblate spheroidal harmonics (OSH). Firstly, we introduce a semi-normalization factor to the second-kind associated Legendre function to ensure equal contribution from each degree function. To avoid calculating complex numbers in the above procedures, a renormalization process is used alongside a recursive expansion of the operation, utilizing a suitable hypergeometric transformation. The first-order and second-order derivative explicit equations are derived. The effectiveness of higher-degree forms (up to 2000) is evaluated to verify the model’s accuracy, and we establish the conversion relation between OSH and SH under semi-normalized coefficients. For the pole singularity, the differential constant equation of P _n (x) is used to eliminate the sinusoidal co-latitude contained in the denominator of MGT. Finally, the high-resolution modeling of MGT is realized. We discuss the distribution of the MGT at the heights of 0.2 km and 300 km, respectively, and draw their spectra. The results of the numerical experiments verify the validity of the model and the accuracy of the calculations at the geographic poles, which are difficult for conventional methods.

Purpose: To compare acute effects of 2 dietary interventions with usual dietary habits on physician trainees’ alertness during overnight shifts. Method: This registered, controlled, block randomized crossover trial (NCT03698123) was conducted between October 2018 and May 2019 at Stanford Medicine. Physician trainees working at least 3 overnight shifts during a 1-week period were recruited. During the first night, participants followed their usual dietary habits. During the intervention nights (low carbohydrate-to-protein ratio and high carbohydrate-to-protein ratio interventions), participants received healthy dinners, snacks, water, and, upon request, caffeinated beverages, at the beginning of their shifts and were instructed to eat meals before 10 Pm. The sequence of interventions on the second and third nights were block randomized across study weeks. Outcome measures (a priori) were overnight changes in validated measures of specific neurobehavioral dimensions: psychomotor vigilance, sensory–motor speed, working memory, and risk decision making, as well as self-reported sleepiness and work exhaustion. Results: Sixty-one physician trainees participated in this study. Compared with usual dietary habits, overnight changes in psychomotor vigilance scores (scale 0–1,000) improved by 51.02 points (95% CI: 12.08, 89.96) and sleepiness (scale 1–7) improved by 0.69 points (95% CI: 0.33, 1.05) under the low carbohydrate-to-protein ratio intervention. Compared with usual dietary habits, overnight changes in sleepiness (scale 1–7) improved by 0.61 points (95% CI: 0.25, 0.96) under the high carbohydrate-to-protein ratio intervention. Neither intervention had beneficial effects relative to usual dietary habits with respect to sensory–motor speed, working memory, risk decision making, or work exhaustion. There were no differences in outcomes between low carbohydrate-to-protein ratio and high carbohydrate-to-protein ratio interventions. Conclusions: Dietary interventions may mitigate negative effects of physician trainee sleep deprivation during overnight shifts. Future studies are warranted to further examine the effectiveness of nutritional strategies on physician alertness during overnight shifts.

The hot-spot temperature of a dry-type air-core reactor is a crucial factor that determines the service life of the reactor. Although the environment elevation has a significant influence on the reactor’s heat dissipation performance and hot-spot temperature, studies seldom focus on the temperature distribution for different altitude scenarios. To this end, this paper proposes a temperature field simulation model with multi-parameter coupling constraints based on the laminar–turbulent flow state. The calculation of the temperature field with the hot-spot temperature at different altitudes is finally achieved. The simulation results show that the hot-spot is located at 6.3% from the top of the sixth encapsulated-winding. It also shows that the hot-spot temperature of the reactor increases by 5 K–11 K with the altitude ascending by 1 km. Moreover, the hot-spot temperature of the reactor exceeds the temperature index at an altitude of 3.25 km, which will result in a shortened service life. Fiber Bragg grating temperature sensors are embedded in encapsulated-windings to detect the temperature for verifying the validity of the temperature field model, which could provide critical temperature rise evaluation rules for the operation safety of the dry-type air-core reactor.

A double-thimble-type fiber Bragg grating (FBG) temperature sensor that isolates the stress strain is developed, and the three materials of air, grease, and copper thimble are employed for encapsulating. To investigate the effect of different encapsulation materials on the time constant of the sensors under dynamic conditions, the transient heat conduction mathematical model is built according to the lumped heat capacity (LHC) system and thermal equilibrium theory, and the time constant is solved by an analytical solution. Then, a proportional three-dimensional sensor simulation model is established and the transient heat transfer process is numerically solved by the finite element analysis method. To verify the models, an experimental system is established to test the response speed of the three-type sensor and the experimental data are compared with the analytical and numerical solution results. The results show that the dynamic response performance depends on the encapsulation material parameters; the response speed is faster than recovery speed; and the response speed of the air packaging sensor is more than 20% faster than that of the grease packaging sensor, and more than 30% faster than that of the copper packaging sensor. The smaller the heat storage capacity and the larger the heat transfer coefficient, the faster the sensor’s response speed.